Category Archives: California Stem Cells

Pressure to create a coronavirus vaccine is increasing by the day, but for a safe vaccine to enter the market, it takes time. USA TODAY

MILWAUKEE In a week whenthe coronavirus closures and quarantines hitlikefalling dominoes the lockdown in Italy,the emptyworkplaces and college campusesin the U.S., suspended sports seasons, canceled festivals far less attention fell on theglobal scientific community's driveto find treatments forthe new virus.

But researchers are already suggesting strategies tohelp patientssuffering from the virus, which is marked by fever, coughing and difficulty breathing. One treatment could be just weeks away.

With no vaccine expected anytime soon, treatmentsarecrucialtosaving the lives of thousands of the infected, especiallyhigh-riskpatients the elderly, those with compromised immune systems and those with chronic illnesses, such as diabetes, heart disease and lung disease.

"I'm very hopeful and very positive. We'll get through this,"said Robert Kruse, a doctor in the Department of Pathology at Johns Hopkins Hospitalin Baltimore. "I've been shocked this week at the measures that have been taken (to alter daily life). They were probably the correct ones, given that they have worked in other countries."

Autoplay

Show Thumbnails

Show Captions

Kruse has been pursuing two treatmentstrategies, one of which has a long history andcould be availablewithinweeks rather than months. The quickest option is likely to be the use ofantibodies from recovered COVID-19 patients. As of Saturday, there were almost 72,000 such patients worldwide. Thevirus has infected about 150,000, killing more than 5,500.

The use of survivor antibodies, serum therapy,dates back to 1891 when it was used successfully to treat a child with diphtheria. Since then, serum from recovered patients has been used "to stem outbreaks of viral diseases such as poliomyelitis, measles, mumps and influenza," according to a paperFriday in The Journal of Clinical Investigation.

"As we are in the midst of a worldwide pandemic, we recommend that institutions consider the emergency use (of serum from recovered patients) and begin preparations as soon as possible. Time is of the essence," wrote the paper's two authors, Arturo Casadevall of Johns Hopkins School of Public Health and Liise-anne Pirofski of the Albert Einstein College of Medicine in New York.

All of the strategies, including the use of serum from recovered patients, have drawbacks. Transfusion of serum carries potential side effects, including fever, allergic reactionsand a very small risk of infectious disease transmission.

Collecting large amounts of serum from recovered patients could be a sizable task. It could turn outthat serum from one recovered patient is enough to save only a singlesick one, explainedKruse at Johns Hopkins. "It's a logistical challenge to put it together, but at the very least there are no hurdles (from the U.S. Food and Drug Administration)to producing the therapy."

Kruse advanced anothertechnique in a paper published in late Januaryin the journal F1000 Research.

His method seeks to take advantage of the new coronavirus' ability to latch onto and enter cells.

Scientists often talk about "cell receptors," which are essentially doors that allow a virus to enter the cell.

The "door" the new coronavirus is entering through is known as the ACE-2 protein. Kruse's technique involves detaching the externalportionof ACE-2, which would act as a decoy for the virus. Thevirus would bind tothe decoy, leaving it unable to reachtheactual door into the cell, and thusunable tocause infection.

"It won't realize, 'Oh gosh, this isn't a cell,'" Kruse explained in an interview. "The virus can't mutate away from this."

Kruse'sdecoy therapy would not be available until fall at the earliest. A similar version of the strategy, however, is being tested now in trials in China.

Afaster optioninvolves what's called "repurposing" a drug.

This is when a drug that has already been found safe and approved fortreatment of one disease also is foundusefulin treating another. One example is thedrug Sildenafil, which is sold as Viagra andused to treat both erectile dysfunction andpulmonary hypertension.

There are three ways in which scientists try to findan existing drug that can treat a new condition.

The rational method involves using drugs that have characteristics and targets that suggestthey might be used to treatthe new condition.

The computational method involves examining protein structures and using them to predict an existing drug that might work.

The final method takes advantage of the vast drug libraries possessed by companies and academic institutions. High-speed technology allows researchers to screen thousands of drugs quickly to determine whether they will act against a specific target.

Considerable hope,interest and money have been invested in one drug not previously approved, remdesivir. The drug was tested against Ebolabut failed in trials.

Gilead Sciences, a biopharmaceutical company based in Foster City, California, announced that two clinical studies of the drugare beginning thismonth. Two more clinical trials of the drug already have begun in China.

In the U.S., the clinical trials process is slow and painstaking, takingseveral years andsometimes much longer.

Another approach to the new virus championed by numerous researchers isthe use oflab-made proteinscalled monoclonal antibodies.

These confer what's called "passive immunity" and have been used beforeto treat cancer, multiple sclerosis,cardiovascular disease and many other conditions.

"The use of monoclonal antibodies is a new era in infectious disease prevention which overcomes many drawbacks associated with serum therapy ... in terms of specificity, purity, low risk of blood-borne pathogen contamination and safety," wrote the authors of a recent paper in the Asian Pacific Journal of Allergy and Immunology.

The biotechnology company Regeneron, based in Tarrytown, New York, started work searching for a monoclonal antibody "for this particular virus in early/mid-January," said Christos Kyratsous, the company's vice president for infectious diseases and viral vector technologies. "But really we started working on it decades ago when we began building our unique end-to-end drug discovery and development technologies."

Gregory Poland, director of Mayo Clinic's Vaccine Research Group, said the use of monoclonal antibodies "needs to be designed and tested in this specific disease, but I wouldn't see any reason it wouldn't work. The idea is right."

Like other scientists, Poland was less hopeful that a vaccine would be developed anytime soon.

"We won't have a vaccine for this outbreak," he said. "It will be before thenext (outbreak)."

Monoclonal antibodies do havepitfalls. They require extensive testing. Also, viruses can mutate and escape from the antibodies. Companies sometimestarget two different parts of the virus to make it harder for the virusto mutate and elude the antibodies.

Ajay K. Sethi,associate professor of population health sciences at the University of Wisconsin-Madison, expressed support for the development of monoclonal antibodies.

"In my opinion, trying a strategy like monoclonal antibodies to provide passive immunity is a good idea," Sethi said.He added that given the technique's past successes, "it is hopeful, but not surprising."

Strategies forcombating the new coronavirus will likely requirereaching patients early before they get too sick. Toward that end, Kruse said he believes the U.S. should pursue the much broader coronavirus testing policythat South Koreaadopted.

"Maybe in the next few weeks we will get to the point where we are testing everyone," he said.

Take a break from coronavirus news: The 12 adorable baby animal photos you need right now

Coronavirus: Here are some TikToks and memes to get you through the panic

Autoplay

Show Thumbnails

Show Captions

Read or Share this story: https://www.usatoday.com/story/news/health/2020/03/15/coronavirus-treatment-could-coming-doctors-say-still-no-vaccine/5052788002/

Excerpt from:
The race to find a coronavirus treatment: One strategy might be just weeks away, scientists say - USA TODAY

SAN FRANCISCO, March 16, 2020 /PRNewswire/ -- The global single cell analysis marketsize is expected to reach USD 8.02 billion by 2027, registering a CAGR of 16.9% during the forecast period, according to a new report by Grand View Research, Inc. Advancements in molecular techniques which resulted in higher accuracy, ability to perform multiple omics analyses in one cell, and automation, has lowered the barriers for implementation of single-cell analysis techniques across various end-use settings. As a result, companies are investing in introducing novel solutions to accelerate the identification and quantification of genetic information in individual cells for research programs, thereby contributing to revenue growth in this market.

Grand_View_Research_Logo

Key suggestions from the report:

Read 150 page research report with ToC on "Single Cell Analysis Market Size, Share & Trends Analysis Report By Product, By Application (IVF, Cancer, Immunology, Neurology, Stem Cell, Non-invasive Prenatal Diagnosis), By End Use, And Segment Forecasts, 2020 - 2027" at: https://www.grandviewresearch.com/industry-analysis/single-cell-analysis-market

This technology has addressed several research challenges with respect to biological intricacies in stem cell biology, tumor biology, immunology, and other therapeutic areas. This leads to improved therapeutic decision-making with regards to precision medicine, thereby driving the adoption of these assays in personalized therapeutic development.

The growth in research publications depicts the increasing R&D investments. Since R&D activities are considered as the foundation of innovation, investments in R&D activities signify a healthy growth prospect for the single cell analysis market. Moreover, the establishment of new single cell genomics centers in the past years is anticipated to boost the uptake of instruments and consumables for single cell analysis, thus driving the growth.

Grand View Research has segmented the global single cell analysis market on the basis of product, application, end use, and region:

Find more research reports on Biotechnology Industry, by Grand View Research:

Gain access to Grand View Compass, our BI enabled intuitive market research database of 10,000+ reports

About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

Contact:Sherry JamesCorporate Sales Specialist, USAGrand View Research, Inc.Phone: 1-415-349-0058Toll Free: 1-888-202-9519Email: sales@grandviewresearch.comWeb: https://www.grandviewresearch.comFollow Us: LinkedIn| Twitter

View original content:http://www.prnewswire.com/news-releases/single-cell-analysis-market-size-worth-8-02-billion-by-2027--cagr-16-9-grand-view-research-inc-301024572.html

SOURCE Grand View Research, Inc.

Go here to see the original:
Single Cell Analysis Market Size Worth $8.02 Billion By 2027 | CAGR: 16.9%: Grand View Research, Inc. - Yahoo Finance

INTRODUCTION

The process of vision starts from the retina, a part of the central nervous system (CNS) that processes both image- and nonimage-forming visual information (1, 2). The retina, composed of multiple types of neurons (photoreceptors, horizontal cells, bipolar cells, amacrine cells, and retinal ganglion cells) and a single type of glial cells (Mller cells) differentiated from retinal progenitor cells (RPCs), is an excellent system for studying the regulation of neurogenesis in the CNS (3, 4). Tremendous progress has been made in deciphering the complex molecular mechanisms underlying retinal neurogenesis in rodents (57). In contrast, knowledge regarding the molecular mechanisms underlying human retinogenesis remains scarce. Recent advances in human retinal studies provide valuable gene expression and epigenetic profiles of the developing human retina (8, 9). However, the transcriptional regulatory network, which can provide insight into the regulation of interactional transcription factors (TFs), remains poorly understood during human retinal development. The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) has emerged as a sensitive and robust method for open chromatin assays, nucleosome site mapping, and TF occupancy analysis (10, 11). Moreover, ATAC-seq is also applicable for establishing the transcriptional regulatory network during development, as integration of known TF motifs with chromatin accessibility data from ATAC-seq can predict a genome-wide regulatory network (10). Therefore, systematic ATAC-seq analysis will be a powerful tool to decipher the epigenetic features and transcriptional regulatory network during human retinal development.

Studies on the underlying regulatory mechanisms of human retinal development have been hampered by the impossibility of direct molecular and genetic manipulation of human retinae in vivo. Retinal organoids (ROs) derived from human induced pluripotent stem cells (hiPSCs) are three-dimensional retinal-like structures grown in vitro, which contain the main cell types and proper apical-basal polarity of retinae (12). Thus, ROs provide an opportunity to study human retinal development and disorders with additional flexibility for molecular and genetic manipulations. Previous studies have applied ROs to mimic disease processes and cell transplantation for retinal regeneration (1315). However, advances in clinical studies using ROs have been hindered by our limited understanding of the molecular and functional differences between the developing human retina and ROs. Furthermore, it is unclear to what extent ROs recapitulate the development of the human retinae in epigenetic modifications. Therefore, it is critical to establish the epigenetic correlations between the developing human retina and ROs.

The dynamics of chromatin accessibility play an important role in regulating human development, including cell fate determination, cell differentiation, and diseases occurrence (16, 17). Recent studies have shown that rod and cone photoreceptors display distinct chromatin accessibility landscapes during fate determination in mice, suggesting that cellular epigenomic states are crucial for retinal neurogenesis (18). In this study, using ATAC-seq and RNA sequencing (RNA-seq) analysis, we explored the chromatin accessibility and transcriptional changes in human retinae and ROs over long-term retinal development. Our results showed that the developing human retina exhibited a complex pattern of chromatin dynamics accompanying retinogenesis. Further analysis indicated that ROs recapitulated the human retinogenesis to a great extent, but divergent epigenetic signatures were found. Moreover, we identified two TFs [nuclear factor I B (NFIB) and thyroid hormone receptor alpha (THRA)] as essential regulators in human retinal development and validated their functions via gene manipulation in ROs. The transcriptional regulatory networks were reconstructed in human and RO, and signaling pathways were analyzed in human and murine retinal development, providing an invaluable data source for future molecular mechanism studies. The chromatin modifications during human and murine retinal development were cross-analyzed and revealed that a bivalent domain of H3K4me3 and H3K27me3 modifications enriched in human only, suggesting a unique and more dedicated epigenetic regulation on human genome. Together, our systematic profiling and integrative analyses of epigenetic and transcriptional changes provide a comprehensive view of the chromatin landscapes that accompany the murine, human retinal, and RO development; establish a developmental temporal-correlation roadmap between the human retinae and ROs; and present a data source for modifying RO culture under the guidance of in vivo human retinal development.

To determine the chromatin accessibility in developing human retina and ROs, the developing human retina from gestational week 6 (GW6) to GW25 at nine time points (GW6, GW10, GW11, GW12, GW14, GW15, GW20, GW24, and GW25; two biological replicates at GW11, GW15, GW20, GW24, and GW25; n = 1 at GW6, GW10, GW12, and GW14), which spanned the key human retinal developmental stages (8), and hiPSC-derived ROs from week 0 to week 30 (w0, w2, w4, w6, w10, w15, w23, and w30; two biological replicates at all stages) were collected for ATAC-seq analysis (Fig. 1A). Each ATAC-seq library was sequenced to obtain, on average, more than 50 million total raw reads per sample. ROs were differentiated as per previous protocols (15). We also conducted RNA-seq for w0, w2, w6, w10, w15, and w23 ROs (n = 1 at all stages). RNA-seq data of the developing human retina were obtained from previous study (8). Here, we stained the developmentally regulated gene RECOVERIN (RCVRN) and nuclear receptor subfamily 2 group E member 3 (NR2E3) in developing human retina and ROs as indicators of differentiation from RPCs to photoreceptors (Fig. 1, B and C, and fig. S1, D and E). Our data revealed that RCVRN protein expression emerged at GW14 and w10 in the human retinae and ROs, respectively, with the expression sustained to GW25 and w30. Like RCVRN, the rod photoreceptor marker NR2E3 was shown at GW20 and w15, respectively. These similar expression trends of the photoreceptor markers indicated that RO culture exhibited progressive retinal neurogenesis, as found in the human retinae.

(A) Schematic illustration of the overall experimental designs. Whole human neural retinae and ROs were collected for ATAC-seq (two replicates labeled with asterisk) and RNA-seq (inverted triangle). Development of human retinae and ROs was grouped into early, middle, and late stages and color coded. Immunostaining of GNAT1 in human retinae GW25 and ROs w30 is shown. Nuclei were stained with 4,6-diamidino-2-phenylindole (DAPI). Undiff, undifferentiated; Early, early developmental stage; Mid, middle developmental stage; Late, late developmental stage. Scale bars, 500 m (bright-field images) and 10 m (fluorescence images). PC1, principal component 1; PC2, principal component 2. (B and C) Immunostaining of RCVRN in human retinae (B) and ROs (C). Nuclei were stained with DAPI. NBL, neuroblastic layer; ONL, outer nuclear layer; INL, inner nuclear layer; GCL, ganglion cell layer. Scale bars, 20 m. (D) Heat map of Pearson correlations across all samples using all ATAC-seq peak signals. Relevant developmental stages are labeled with distinct colors as in (A). (E) PCA of chromatin accessibility during human retinal (blue) and RO (red) development in two dimensions. The black dotted arrow indicates the development process of retinogenesis. (F and G) Normalized epigenetic and expression profiles at the RCVRN loci during human retinal development (F) and RO differentiation (G). All signals were obtained from the University of California, Santa Cruz (UCSC) genome browser. (H) qRT-PCR analysis of the expression level of RCVRN (n = 3) during RO differentiation. Data are means SEM. One-way analysis of variance (ANOVA) was performed. ****P < 0.0001.

The ATAC-seq data were analyzed using the ATAC-pipe (19) to obtain the chromatin accessible sites in the developing human retina and RO. Transcription starting site (TSS) enrichment from all samples, aligned fragment length distribution of all samples, and correlation analysis of all the replicate samples indicated high-quality data and excellent reproducibility between replicates (fig. S1, A to C). We also performed correlation analysis of the ATAC-seq peak intensities to define the similarities in chromatin accessibility between the human retinae and ROs (Fig. 1D). The sample replicates were strongly clustered with each other, confirming the high reproducibility of the experiments. Here, except w0 (the undifferentiated hiPSCs), the entire retinal development process can be grouped into three time periods, that is, the early (GW6; w2 to w6), middle (GW10 to GW14; w10 to w15), and late (GW15 to GW25; w23 to w30) stages (color coded in Fig. 1, A and D, and fig. S1F), indicating that human retinae and ROs were developmentally correlated in chromatin accessibility. In addition, the ATAC-seq peaks were also clustered with deoxyribonuclease I (DNase I) hypersensitive site sequencing (DHS-seq) data in day 74 (D74) (DHS-GW11) and D125 (DHS-GW18) retinae produced by the encyclopedia of DNA elements (ENCODE, http://www.encodeproject.org/) project (Fig. 1D). Principal components analysis (PCA) revealed that the development trajectories of the human retinae and ROs were temporally related in two dimensions. Similar results were found by uniform manifold approximation and projection (UMAP) analysis (Fig. 1E and fig. S1F). Together, these findings suggested the developmental relevance between human retinae and ROs. However, note that although ROs and human retinae were clustered together in the middle stage, the two groups were split apart (fig. S1F, light yellow coded with white dot line), suggesting that the epigenetic signatures might be slightly different between human retinae and ROs at this stage.

We next investigated whether chromatin accessibility was related to gene expression changes. As a positive control, we found elevated enrichment of the ATAC-seq and DHS-seq signals at putative promoters and enhancers at the RCVRN gene locus, consistent with the stages when the gene was expressed (Fig. 1, F and G). Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) quantified the expression level of RCVRN in ROs during the differentiation process (Fig. 1H), confirming consistency between the enrichment of RCVRN expression and chromatin dynamics obtained from the ATAC-seq data. In addition, NR2E3 also showed consistency in chromatin accessibility and gene expression dynamics during human retinal and RO development (fig. S1, G and H). Collectively, our data suggested that RO differentiation recapitulated human retinal development to a great extent. On the basis of the chromatin accessibility profile of developing human retina and ROs, we established the maps of the temporal correlation between the human retinae and ROs.

To delineate how epigenomic dynamics governs human retinal development, we applied pairwise comparisons of the ATAC-seq signals of human retinae and ROs at different developmental time points. We discovered 10,563 differential DNA accessible sites across the genome (8805 elements from human retinae and 10,160 elements from ROs) and identified five distinct regulatory element clusters (C1 to C5) via unsupervised hierarchical clustering (Fig. 2A). To understand the functions of these notable differential peaks, we applied Gene Ontology (GO) term enrichment analysis using GREAT v3.0.0 (20). GO analysis of the C1 to C5 cluster peaks revealed three main functional groups for the differential accessible sites: The first functional group included C1 and C2, which were composed of 1636 and 2759 elements, respectively. These peaks were highly accessible in the beginning (GW6 and w0 to w6) but progressively declined with human retinal and RO development. GO analysis identified that these peaks were associated with early retinal development, such as neural tube formation (P < 1 105), neural tube closure (P < 1 105), regulation of neuron differentiation (P < 1 107), and neural precursor cell proliferation (P < 1 106) (fig. S2, A and B). Because C3 consisted of only 478 peaks and showed no enriched GO terms, peaks in C3 were not further analyzed. The second major functional group was C4, which was composed of 3065 peaks. These C4 peaks were accessible from the middle developmental stage (GW10) and sustained to the late stage (GW25) in the human retinae. Strikingly, the C4 peaks were accessible only in the late RO developmental stage (w23 to w30). GO analysis revealed that the peaks in C4 were strongly enriched in nervous system development, including neurogenesis (P < 1 1060) and neuron differentiation (P < 1 1042) (Fig. 2B), suggesting their key roles in retinal neurogenesis. The third functional group was C5, which included peaks that were not accessible in the beginning but were gradually established during the late developmental stage of both human retinae and ROs (GW15 to GW25 and w10 to w30). The C5 group included 2624 peaks enriched in sensory perception of light stimulus (P < 1 108), visual perception (P < 1 107), and photoreceptor cell differentiation (P < 1 106), which represented the functional maturation of the human retinae, especially the photoreceptors (Fig. 2C). Thus, the GO terms from these three functional groups represented the sequential retinogenesis in human retinae, and the classification of chromatin accessibility provided the possibility to define the timing of key developmental events during human retinal and RO development. From the chromatin accessibility data, we observed that in vitro RO differentiation recapitulated the in vivo human retinal development to a great extent. However, note that the peaks in C4 opened later in RO differentiation than those in human retinal development. It is likely that the distinct pattern of C4 provided possible clues to direct RO differentiation closer to human retinae by genetic manipulation of the regulators related to the C4 peaks.

(A) Heat map of 10,563 differential regulatory elements during human retinal and RO development. Each column is a sample, and each row is a peak. Color scale shows the relative ATAC-seq peak intensity centered at the summit of each peak. Distance of cluster peaks to their nearest gene promoters is shown on the right. (B and C) Significant GO terms enriched in C4 (B) and C5 (C) cluster peaks using GREAT v3.0.0. The number of genes enriched in GO terms is shown in the parentheses. (D) Comparison of open-ended DTW analysis between human retinae and ROs. There were 3235 DEGs in humans. Gene expression data were subjected to open-ended DTW analysis, with results plotted as a heat map. (E to H) Violin plot representing the expression level of genes closest to the top 1000 peaks in C1 (E), C2 (F), C4 (G), and C5 (H) during human retinal development showing a variable but positive correlation between chromatin accessibility and gene expression. GREAT was used to annotate peaks to genes. Statistical significance was analyzed with one-way ANOVA. ***P < 0.001, ****P < 0.0001.

We also performed pairwise comparisons of RNA-seq analysis of developing human retina and ROs (fig. S2C). We identified distinct G1 to G4 clusters in the RNA-seq data. Genes in the G1 cluster were associated with early developmental processes, such as cell division, DNA replication, and mitotic cell cycle. G2 genes were associated with axon guidance and regulation of neuron projection development. Genes in G3 were related to visual perception and phototransduction. G4 genes exhibited nonspecific biological processes with retinal development; thus, G4 was not used for further analysis. Therefore, the GO terms (G1 to G3) of RNA-seq data revealed similar sequential retinal development between human retinae and ROs. To further compare the human retinal and RO transcriptome during retinal development, we performed open-ended dynamic time-warping (OE-DTW) analysis (21) of 3235 differentially expressed genes (DEGs) from human retinae (Fig. 2D). We observed a tight temporal correlation between human retinae (GW7 to GW20) and ROs (w0 to w23), confirming that human retinae and ROs shared considerable similarities in gene expression changes. We next examined whether the chromatin signatures in different clusters (C1 to C5) were correlated with the corresponding gene expressions. We chose the top 1000 peaks in each cluster and then applied GREAT to obtain a list of genes regulated by the ATAC-seq peaks and correlated their expression values. By combining the ATAC-seq profiles with the RNA-seq data during retinal development, genes near the loci that gained chromatin accessibility showed significant increases in gene expression levels, whereas genes near the loci that lost chromatin accessibility exhibited decreased expression (Fig. 2, E to H, and fig. S2, D to G), indicating a high correlation between epigenetic and RNA profiling. The correlation between epigenetic and RNA profiling was further analyzed on cell lineage markers, such as PAX6 (retinal progenitor marker), GNAT1 (rod marker), GNGT2 (cone marker), GLUL (Mller cell marker), PROX1 (horizontal cell marker), TFAP2A (amacrine cell marker), and VSX1 (bipolar cell marker) (fig. S3, A to G). Most of the markers showed the similar trends in chromatin accessibility and gene expression during retinal development, suggesting that the chromatin accessibility may govern the gene expression. Together, we observed sequential chromatin changes associated with retinogenesis and correlated with gene transcription; thus, the developmental transitions during retinogenesis can be reflected in the epigenome dynamics.

To identify potential TFs involved in human retinal development, we searched for TFs enriched at accessible sites in C1, C2, C4, and C5 using HOMER v4.8. As accessible DNA sites are often obligated if TFs bind to their cognate DNA motifs, the integration of TF motifs and DNA accessibility data from ATAC-seq can predict TF occupancy on chromatin and thus create regulatory networks (16, 17, 22, 23). Our data revealed distinct patterns of TFs in different clusters. The TFs enriched in the C1 and C2 peaks were identified as potential regulators of early retinal development (fig. S4, A and B). For example, PAX6 is a key regulator for maintaining the multipotency of RPCs (24). SOX3 and RUNX are well known for self-renewal maintenance and morphogenesis (25, 26).

The TFs enriched from C4 and C5 ATAC-seq peaks were identified as critical regulators for neuronal and photoreceptor differentiation, respectively (Fig. 3, A and B). For instance, cluster C4 was enriched with VSX2, SMAD2, and NEUROD1, which are important for retinal neurogenesis (2729). C5 was enriched with OTX2, CRX, and NR2E3, which are key regulators of photoreceptor differentiation. OTX2 is required for RPC differentiation and cell fate determination (30, 31). CRX is a key regulator for the survival and differentiation of photoreceptors (32). NR2E3 is a direct target of NRL involved in rod and cone photoreceptor differentiation in rodents (33). Therefore, the TFs predicted from the ATAC-seq data were highly associated with retinogenesis and differentiation.

(A and B) TF motifs enriched in C4 (A) and C5 (B) peaks, with P values estimated from HOMER v4.8. (C) Predictions of TFs that may regulate human retinal development (left) and RO differentiation (right). TFs known to be involved in regulating retinal development are shown on top (red). The color of each circle represents expression level of genes that encode corresponding TFs, and the size of the circle represents the enrichment of the motifs. Relevant developmental stages are labeled with distinct colors as in Fig. 1A. (D) Visualization of ATAC-seq footprint for motifs of ASCL1, CRX, NFIB, and THRA in four developmental stages of human retinae. ATAC-seq signals across all motif binding sites in the C4 and C5 genome regions were aligned on the motifs and averaged.

Since C4 and C5 peaks were associated with the middle and late stages of retinal development, which were important for neurogenesis and phototransduction, we focused on C4 and C5 to search for previously unknown neurogenesis regulators. One caveat of only using motif analysis for TF prediction is that TFs or TF families can share the same motif; therefore, we integrated motif enrichment analysis by ATAC-seq data and gene expression profiles from the RNA-seq data to better predict the TF occupancy on accessible sites of C4 and C5. At each time point, we plotted the expression value and motif enrichment score on the same figure (Fig. 3C), which showed that many well-known photoreceptor development TFs were highly expressed, and their motifs were enriched at the middle and late stages (GW10 to GW20 and w10 to w23), including CRX, OTX2, ASCL1, and NR2E1. We found TFs NFIB and THRA, which showed similar high expression and motif enrichment at the middle and late retinal developmental stages. NFIB and THRA have not been reported in photoreceptor differentiation. Therefore, to evaluate their involvement in retinal development, we studied all differentially expressed downstream genes containing the binding motifs of NFIB and THRA together with two well-known retinal development regulators (ASCL1 and CRX) as the control (fig. S4C). GO analysis indicated that up-regulated downstream targets of all four factors were involved in retinal development, including visual perception and phototransduction. Thus, NFIB and THRA may participate in the regulation of retinal development.

To further refine our prediction of the potential regulators of retinal development, TF footprint analysis of the ATAC-seq data, which provides evidence of direct occupancy of TF candidates on genomic DNA, was performed. DNA sequences directly occupied by DNA binding proteins are protected from transposition during library construction in ATAC-seq, and therefore, the resulting sequence footprint reveals the presence of a DNA binding protein at its binding sites, analogous to DNase digestion footprints. We illustrated the footprints of two known regulators, ASCL1 and CRX, and observed deeper footprints and higher DNA accessibility flanking their motifs in the late stage compared with the early stage of human retinal and RO development (Fig. 3D and fig. S4D). Notably, the footprints of NFIB and THRA were also deeper and more accessible at the late stage, suggesting that the motifs of these two TFs were not only enriched at stage-specific peaks but also most likely physically bonded to the chromatin accessible sites, indicating that they were possible functional regulators of human retinal and RO development. Collectively, the orthogonal footprint results were consistent with the motif enrichment results, indicating that NFIB and THRA were potential previously unidentified regulators of retinal development.

As ROs were similar to human retinae in gene expression and chromatin accessibility, we used ROs as a model to investigate the potential role of NFIB and THRA during retinal development. We established an electroporation method to efficiently overexpress or knock down target genes in ROs. The outer regions of bright neuroretinal epithelium in ROs were cut into ~500-m (diameter) pieces and placed into cuvettes for electroporation (Fig. 4A). Electroporated RO samples were collected for qRT-PCR or RNA-seq analysis on D10 after electroporation (Fig. 4B). We investigated the function of three genes, CRX, NFIB, and THRA, in retinal development. As a positive control and to test our electroporation system, CRX was knocked down in ROs around w14 and overexpressed around w7. The qRT-PCR results indicated that CRX knockdown (CRX_KD) reduced the expressions of NRL and RAX2, which were targets of CRX related to photoreceptor differentiation (fig. S5A). Conversely, overexpression of CRX (CRX_OE) markedly elevated the expressions of NRL, ARR3, and OPN1SW (fig. S5, B and C). Both CRX_KD and CRX_OE experiments suggested that our system can successfully manipulate gene expression in RO for studying retinal development. GO analysis of down- and up-regulated DEGs of CRX_OE samples suggested that CRX is involved in visual perception (fig. S5, D and E). Thus, these results indicated that we established a reliable gene manipulation system in ROs. Next, specific short hairpin RNA (shRNA) vectors for NFIB or THRA knockdown were electroporated into ROs at ~w14, a time point when NFIB and THRA were expressed. We revealed significantly decreased expression of NFIB and THRA by qRT-PCR or RNA-seq analysis (Fig. 4C and fig. S5, F and G), respectively. To validate the functional knockdown of these two TFs, we next analyzed the expression level of EZH2, a known target of NFIB, and ARNTL, a potential target of THRA. Results revealed that the expressions of EZH2 and ARNTL decreased significantly due to loss of NFIB and THRA, respectively (Fig. 4C and fig. S5G). Notably, we found that a set of photoreceptor-associated genes were down-regulated, including CRX, RHO, and GNAT1, under knockdown of NFIB and THRA, suggesting that NFIB and THRA may be involved in regulating photoreceptor differentiation (Fig. 4, C and D, and fig. S5G). NFIB is highly expressed in fetal cerebral cortex neural progenitor and glial cells and is required for neuronal and glial differentiation in the fetal cerebral cortex (34). Considering that neurogenesis regulation in the CNS is conserved, we selected NFIB for further functional studies. The RNA-seq of NFIB knockdown (NFIB_KD) ROs revealed many down-regulated retinogenesis genes, including GNAT1, NR2E3, and GNGT2 (Fig. 4D). GO analysis of down- and up-regulated genes in NFIB_KD RNA-seq strongly suggested that NFIB was required for retinal development, especially for photoreceptor differentiation (Fig. 4, E and F). In addition, we further used immunohistochemistry to detect the NFIB_KD effect on highly expressed photoreceptor-related protein, RCVRN, between w14 and w15 (Fig. 4G). The quantification results of the relative intensity of RCVRN implied that NFIB_KD reduced the protein expression of RCVRN (Fig. 4H). Similarly, the percentage of RCVRN-positive cells also reduced accordingly in NFIB_KD ROs (Fig. 4I). Together, these data demonstrated that NFIB and THRA were involved in human retinal and RO development. It is possible that NFIB and THRA affected the self-renewal and differentiation ability of RPC to photoreceptors and Mller cells. However, the hypothesis needs to be further investigated.

(A) Schematic illustration of ROs split into small sheets for electroporation. Dotted line represents clipping path. (B) Representative images of RO sheets transfected with reported plasmids 10 days after electroporation. Scale bar, 500 m. (C) qRT-PCR analysis of expression levels of genes after knockdown of NFIB (n = 5). Data are means SEM. (D) Plot representing DEGs between control and NFIB_KD groups. Significantly up- and down-regulated genes (fold change >1.5) are highlighted in red and blue, respectively. (E and F) Significant GO terms enriched in down- (E) and (F) up-regulated genes, respectively, in the NFIB_KD experiment. The number of genes enriched in GO terms is shown in the parentheses. (G) Immunostaining of RCVRN in NFIB_KD ROs and control ROs, respectively. Scale bars, 20 m. (H) Relative intensity of RCVRN signals in the control (n = 366 cells from five independent ROs) and NFIB_KD (n = 135 cells from four independent ROs) groups. (I) Percentage of RCVRN-positive cells in the control (n = 5 independent ROs) and NFIB_KD (n = 4 independent ROs) groups. All statistics by two-tailed Students t test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

To further understand the molecular mechanism underlying NFIB-regulated retinal development, we analyzed the potential NFIB-regulated pathways and related functions by ingenuity pathway analysis (IPA) via comparing the gene expression between NFIB_KD ROs and their control (fig. S6A). The results revealed that phototransduction-associated pathways/functions were enriched in down-regulation genes, further confirming the regulation of NFIB of photoreceptors. Moreover, we examined the potential binding of NFIB to retinal developmentrelated genes. We selected the genes enriched in the highlighted pathways in fig. S6A. We then searched for the binding sites of NFIB in the peak region around these genes. To better determine the possibility of these genes bonded by NFIB motifs, we then define their binding affinities using their signals of footprint flank divided by footprint depth signaling (fig. S6B). The results showed that PROM1 and NR2E3 had high affinity with NFIB motifs. NFIB motifs occupying the gene PROM1 and NR2E3 loci also showed opening chromatin states (fig. S6, C and D); therefore, PROM1 and NR2E3 were potential target genes of NFIB. Overall, NFIB is highly possibly involved in retinal development by regulating photoreceptor-related targets.

TFs often work in a network by cross-talking with each other to regulate gene transcriptions. To establish the potential connection of enriched TFs, we reconstructed a global picture of the TF regulatory networks during human retinal and RO development. First, we used HOMER v4.8 to identify the enriched TFs bound to the C1 to C5 peaks (P < 1 1020). The connections (edges) between TFs were defined as follows: If TF-Xs motif were on the promoter of TF-Y, then TF-X regulated TF-Y, thereby drawing an arrow from TF-X to TF-Y. Here, only TFs distinctly expressed at this time point were considered. On the basis of this rule, we constructed the transcriptional regulatory networks of human retinae (GW6, GW10, and GW20) and ROs (w6, w10, and w23) at the early, middle, and late stages, respectively (Fig. 5, A and B, and fig. S7, A to D). The regulatory networks at the different time points were highly dynamic. For example, the TFs in the GW6 network, including LHX2 and ISL1, which are required for early retinal development (3537), were initially highly expressed. However, during development, the expression and enrichment levels of these TFs were reduced. In contrast, in the GW20 network, many known TFs, such as CRX, NR2E3, and VSX2, were increasingly enriched, confirming their important roles in photoreceptor maturation at the late stage. NFIB and THRA were also enriched in the TF network in the late stage and had connections with other TFs involved in retinal development (Fig. 5, A and B). Since TFs interact with different specific TFs to expand their regulatory repertoire and perform regulatory functions, the edge (connection) counts of each TF may represent its importance in regulating retinal development. To better represent the importance of TFs in a network, we defined the connection score of each node in the network as its edge counts multiplied by the SD of its expression (Fig. 5, C and D, and fig. S7, E to H). For example, TFs with the top connection score, such as VSX2, NR2E3, and CRX, are well-known regulators in retinal development. NFIB and THRA were also observed with high connection score, suggesting that NFIB and THRA are also important in retinal development. The TF networks from the human retinae and ROs were highly correlated from early to late developmental time points (Fig. 5E). However, the TF networks in the middle stage showed relatively lower correlations, which may be due to the distinct C4 chromatin accessibility (Fig. 2A) between human retinae and ROs.

(A and B) Cis-regulatory networks of TFs (nodes) in human retinae GW20 (A) and ROs w23 (B). Circle groups from inner to outer represent different time points. Arrow on edge from node X to node Y indicates that TF-X regulates TF-Y by binding to the promoter site of the latter. Size of each node indicates TF enrichment, and color of each node indicates TF expression levels in that stage. Connection types indicate Pearson correlation between gene expression profiles of connected TFs. (C and D) Ranking of the connection score in human retinae GW20 (C) and ROs w23 (D) networks. The connection score of each node was defined as SD of its expression multiplied by its degree. (E) Similarity of human retinal and RO networks in different developmental stages. We selected GW6/w6, GW10/w10, and GW20/w23 to represent the early, middle, and late stages of retinal development and calculated their similarity score, respectively.

To determine the distinct epigenetic modifications during human and murine retinal development, mouse DHS-seq data at three time points [embryonic day (E14.5), postnatal day 0 (P0) and P7] were downloaded from ENCODE, which can be clustered into five clusters (MC1 to MC5) (fig. S8A). There was no GO term enriched in MC1. The GO terms of MC2 and MC3 showed that they were involved in stem cell proliferation and regulation of cell development, similar to C1 and C2 in Fig. 2A. MC4 was involved in neurogenesis similar to C4, and MC5 was required for visual perception similar to C5. To decipher the similarity between human and murine retinal development in chromatin accessibility, we chose the top 500 peaks in each cluster and then applied GREAT to obtain a list of genes regulated by these ATAC-seq or DHS-seq peaks. The ratio of overlapping genes from human and mouse clusters was calculated (fig. S8B). The results indicated that genes in C1 and C2 were highly overlapped with MC2 and MC3, and genes in C4 and C5 were overlapped with MC4 and MC5.

Then, we coanalyzed human ATAC-seq data or mouse DHS-seq data with chromatin immunoprecipitation sequencing (ChIP-seq) data in the study by AlDiri et al. (9) during retinal development. Eleven chromatin hidden Markov modeling (chromHMM) states (9) were copy used to systematically annotate the epigenetic states across the C1 to C5 (except C3) and MC2 to MC5 regions during retinogenesis (Fig. 6, A and B). State 1 has active epigenetic marks, states 2 and 3 are predominantly enhancers, and state 4 marks bivalent promoters. State 5 is defined by PolII binding, and states 6 and 7 are consistent with gene bodies (H3K36me3). State 8 is a polycomb-repressed chromatin (H3K27me3) outside of the promoter or enhancers. State 9 is empty chromatin, and state 10 marks the H3K9me3-repressed chromatin. State 11 is marked by the insulator protein CCCTC-Binding Factor (CTCF). The results revealed that in murine retinal development, the chromatin accessible sites were mainly regulated by the active promoter/enhancer marks (state 2), whereas the modifications on human genome were diverse. In human retinal development, the active promoter/enhancer marks (states 2 and 3) were involved in C1 and C2 regulation, which progressively decreased during development. States 1 and 4 highly marked C4, and C5 was mainly marked by state 2. It was likely that active epigenetic states were highly associated with chromatin accessibility during both human and murine retinal development. A similar phenomenon was also detected in cell type markers, such as retinal progenitor marker RAX, rod photoreceptor marker NR2E3, cone photoreceptor marker RXRG, and Mller cell marker GLUL (fig. S8C). The peaks from either ATAC-seq or DHS-seq in these markers were mainly modified by active states, such as states 1 and 2, during both human and murine retinal development.

(A and B) Heat map of different ChromHMM state enrichment in each cluster during human (A) and murine (B) retinal development. Each column is a sample, and each row is a ChromHMM state. Color scale shows the relative enrichment. Each state is used to represent the ChromHMM states (rectangle on the right). (C and D) Heat map of H3K4me1, H3K4me3, and H3K27me3 signals for differential regulatory elements in each cluster during human (C) and murine (D) retinal development. Each column is a sample, and each row is a peak region. Color scale shows the relative ChIP-seq peak intensity centered at the summit of each peak. (E) Significant GO terms enriched in bivalent subgroup and H4K4me3-only subgroup peaks using GREAT v3.0.0. The number of genes enriched in GO terms is shown in the parentheses. (F) Violin plot representing H3K4me1 ChIP-seq peak intensity in bivalent subgroup peaks and H4K4me3 subgroup peaks. (G) TF motifs enriched in bivalent subgroup peaks, with P values estimated from HOMER v4.8. (H) Normalized H3K4me3 and H3K27me3 profiles at NFIB and THRA loci during human retinal development. All signals were obtained from the UCSC genome browser.

The bivalent modifications (state 4) marked C4 peak regions specifically in human retinal neurogenesis but not in mouse MC4. To clearly present the dynamic changes of different histone modifications during both human and murine retinal development, we calculated the signals of histone modifications in each cluster (Fig. 6, C and D). The histone modification signals of H3K4me3 and H3K27me3 were enriched in C4 open regions. However, no such notable bivalency modifications were enriched in mouse MC4. These data suggested that the bivalent H3K4me3 and H3K27me3 modifications are distinguished between human and mouse during retinal neurogenesis, which indicate that developing human retina had a more dedicated epigenetic regulation than mouse due to the co-operation of these histone modifications on genome. The bivalent domains were considered to poise the expression of developmental genes, which allowed timely activation while maintaining repression in the absence of differentiation signals (38), matching the critical role of C4 in neurogenesis.

Next, we divided C4 into two subgroups, namely, bivalent subgroup (H3K4me3 and H3K27me3) and H3K4me3-only subgroup, according to the enrichment of different histone modifications in peak regions (Fig. 6E). GO analysis found that the bivalent subgroup was significantly associated with organ development, generation of neurons, and developmental process, suggesting the important role of bivalency in neurogenesis. The H3K4me3-only subgroup was enriched in phosphorylation and guanosine triphosphatase (GTPase)mediated signal transduction, which were involved in general biological process. As expected, we observed H3K4me3-only enrichment in wildly expressed gene PDK2, which functions as a mechanotransducer that stimulates an increase in intracellular calcium in response to fluid flow (39), whereas the bivalent domain of H3K4me3 and H3K27me3 was detected on the developmental gene BMP8B (fig. S8, D and E), further confirming the important role of bivalent domains in neurogenesis. H3K4me1 is one of the critical modifications for neurogenesis (9). Consistent with this, the C4 bivalent subgroup had more H3K4me1 signals than the C4 H3K4me3-only subgroup (Fig. 6F), further confirming the key role of the C4 bivalent subgroup in neurogenesis. Using motif analysis, we predicted the TFs that regulated the motif with bivalency domains (Fig. 6G). Well-known developmental TFs (OTX2/CRX) and proliferation TFs (c-Myc) were enriched in the bivalent subgroup, which are crucial for various regulations of retinal neurogenesis. Since we determined the role of NFIB and THRA in retinal development, we further investigated the histone modifications around their chromatin regions (Fig. 6H). As expected, NFIB and THRA were bivalently modified with H3K4me3 and H3K27me3, further confirming that these factors were involved in retinal neurogenesis. Together, the bivalent histone modifications in C4 were highly associated human retinal neurogenesis but were relatively weak or missing in mice.

We next used GREAT to decipher the key signaling pathways that were differentially activated during human and murine retinal development (fig. S9, A and B). In early human retinal development, the heparan sulfate proteoglycan (HSPG)/fibroblast growth factor (FGF) signaling pathway was enriched. In agreement, the FGF pathway played a number of roles in eye development, including patterning of the optic vesicle, proliferation and differentiation of progenitor cells, and survival of neurons and photoreceptors. Cell surface heparan sulfate (HS) acts as a co-factor for FGF signaling, forming a trimeric complex with FGF and the FGF receptor. It is therefore expected that the HSPG/FGF pathway was discovered in human retinal development. In the early murine development, several known pathways were identified to be involved in retinal development, including Notch, Wnt and E-cadherin pathways. Notch signaling is an important component of RPC maintenance and Mller cell specification during development. Wnt signaling pathway is a known key regulator of optic vesicle establishment, cornea and lens development, and maintenance of retinal stem cell and neuronal specification. Here, histone deacetylase (HDAC) pathway was also emerging as an important regulator for early retinal development in our pathway analysis. Histone acetylation is a posttranslational modification that leads to changes in chromatin structure and transcription repression, which can regulate retinal fate determination. The roles of HDACs in retinal development need further study. In the middle stage of retinal development, pathways including neuronal system, axon guide, and adenylate cyclase activating were enriched. In the late retinal development, we identified a visual transduction pathway, an Na+/Cl-dependent neurotransmitter transporter pathway, and so on, which related with phototransduction or synaptogenesis. The chromatin accessibilities of the genes involved in different signaling pathways matched with their role in retinal development (fig. S9, C and D). The average expression levels of the genes in each pathway were shown, which matched with their functions in retinal development (fig. S9E). Combined, we were able to generate robust genomic, transcriptomic, and epigenomic datasets, which provided a foundation for future studies for retinal development.

Here, we performed a comprehensive assessment of chromatin accessibility and transcriptional changes during human retinogenesis in vivo and in RO differentiation in vitro and revealed stage-specific chromatin dynamics, which regulate human retinogenesis in line with global transcriptional changes. We reconstructed the transcriptional regulatory network and signal pathways regulating human retinogenesis. Notably, we also identified TFs, NFIB, and THRA involved in retinal development, validated by in vitro gene manipulation in the ROs. Therefore, our study provides valuable data for studying human retinal and RO development and a viable framework to optimize in vitro RO differentiation. Moreover, we showed the difference in epigenetic regulation between human and mice. This kind of difference probably contributes gene expression pattern and timing, giving the species difference in retinal development. Therefore, this study gives valuable information to understand species-specific epigenomic regulation.

In our study, we established a temporal-correlation relationship between human retinal and RO development according to epigenetic and transcriptomic profiles (Figs. 1D and 2D). ROs recapitulated the time courses of retinal morphogenesis, retinal neurogenesis, and photoreceptor differentiation of human retinae in the early, middle, and late stages. Hence, our study provided a correlation time frame for the study of stage-specific human retinal development in the RO system. The high transcriptome and chromatic accessibility similarities between human retinae and ROs indicate that ROs are a good model to study human retinal development. Likewise, the human retinal epigenomic and transcriptomic data provide molecular insights for the further improvement of RO differentiation. It is worth noting that the distinct C4 pattern in developing human retina could be related to the complexities of cell types and differential processes in human retinae. Thus, to improve the RO culture, further studies should focus on the DEGs related to C4 particularly.

The transcriptional regulatory networks were reconstructed in both human retinae and ROs. In these networks, we observed many known key TFs for human retinal development, such as OTX2, NR2E3, and ASCL1, which are also critical for retinogenesis in murine. Therefore, the TFs regulating retinal development are conserved among humans, murine, and ROs. We also observed that the TF networks were highly correlated between the developing human retina and ROs, further confirming that the RO system is a good model to study retinal development. Moreover, NFIB and THRA were identified as potential regulators involved in retinogenesis. Thus, the transcriptional regulatory network expands our understanding of molecular regulation during human retinal development. Previous studies have demonstrated that NFIB plays an important role in regulating neural progenitor cell proliferation and differentiation in the cortex (40). Nfib function was very recently verified in regulating cell cycle and the differentiation of late-born retinal progenitors in mice, further supporting our prediction of the function of NFIB, and suggested the reliability of our data analysis (41). In our study, loss of NFIB at the middle retinal differentiation stage reduced the expression of photoreceptor-associated genes. From pathways and motif analysis, we identified that PROM1 and NR2E3 might be the potential targets of NFIB, partially explaining how NFIB regulates human retinogenesis. The thyroid hormone receptors TR1 and TR are encoded by the genes THRA and THRB, respectively. THRB plays important roles in cone photoreceptor development (42, 43). However, whether THRA is also involved in human retinal development remains unclear. In our transcriptional regulatory network, we found that THRA may interact with NR2E3, VSX1, and CRX, which are well-known regulators in retinal development. We also demonstrated the role of THRA in retinal development via RO molecular manipulations. The function of THRA in retinal development, which has not been reported previously, may be due to the compensatory effects of THRB. The genesis of Mller cells and photoreceptors in ROs detected by immunostaining started after w14, around w17 (15). Here, we knocked down NFIB and THRA at ~14-week-old ROs, which mainly contained retinal progenitors but limited cell numbers of Mller cells (RLBP+) and photoreceptors (GNAT1+ or RHO+). Therefore, it is highly possible that NFIB and THRA mainly function in regulating retinal progenitor differentiation, thereby affecting both the photoreceptor and Mller differentiation.

Histone modifications are crucial for the control of gene expression, cell fate decisions, and differentiation. Many chromatin regions in embryonic stem cells and early embryonic development harbor a distinctive histone modification signature that combines the active H3K4me3 and the repressive H3K27me3 marks (44). These bivalent domains are considered to poise the expression of developmental genes, allowing timely activation while maintaining repression in the absence of differentiation signals. Here, in human retinal development, C4 is bivalently modified and associated with human retinal neurogenesis only, demonstrating a fine-tuning on the gene expression that associated human neurogenesis. Thus, these bivalent features in C4 may facilitate neurogenesis via timely gene activation and silencing. Moreover, cross-analysis with ATAC-seq, RNA-seq, and pathway analysis highlighted numerous signaling pathways, which seemed to be differentially activated in retinal development. The differential activation of these pathways is consistent with changes in the expression of key genes in long retinal development, providing potential regulators involved in retinal development. Thus, our data provided a large scope of data sources for further molecular study underlying retinal development.

In summary, we provided a comprehensive view of the chromatin landscapes that accompany human retinal and RO development; established a comprehensive resource for temporal and molecular correlations between human retinal and RO development; discovered TFs for human retinal development; and reconstructed the transcription regulatory network and signaling pathways, which greatly expand our understanding of human retinal development and provide a roadmap for further studies.

Human embryo collection was approved by the Reproductive Study Ethics Committee of Beijing Anzhen Hospital (2014012x). All embryos were obtained with written informed consent signed by the patient who had made the decision to legally terminate her pregnancy. Informed consent confirmed that the patients were voluntarily donating embryos for research on human embryonic development mechanisms with no financial payment. The deidentified fetal retinae were collected with patient informed consent in strict observance of the legal and institutional ethical regulation approved by the Institutional Review Board (ethics committee) at the Institute of Biophysics, Chinese Academy of Sciences. All samples used in these studies had never been involved in previous procedures (drugs or other tests). All protocols followed the Interim Measures for the Administration of Human Genetic Resources administered by the Chinese Ministry of Health.

Fetal retinae were collected in ice-cold artificial cerebrospinal fluid, which included 125.0 mM NaCl, 26.0 mM NaHCO3, 2.5 mM KCl, 2.0 mM CaCl2, 1.0 mM MgCl2, and 1.25 mM NaH2PO4 (pH 7.4), bubbled with carbogen (95% O2 and 5% CO2). Retinae were gently cut into small pieces, and tissue samples were centrifuged for 5 min at 500g at room temperature (RT). The supernatant was removed followed by the addition of 900 l of 0.25% trypsin-EDTA (Thermo Fisher Scientific, 25200114) with 5 l of DNase I (Thermo Fisher Scientific, EN0521) for digestion for 15 min at 37C. Shaking and gentle pipetting were performed at 5-min intervals. We added 100 l of fetal bovine serum (FBS; Thermo Fisher Scientific, 10270) to stop digestion. Samples were centrifuged and washed with 1 ml of Dulbeccos phosphate-buffered saline (DPBS; Thermo Fisher Scientific, 14190250). We collected ~50,000 cells for ATAC-seq and ~1 million cells for RNA-seq.

The BC1eGFP (enhanced green fluorescent protein) (45) hiPSC line was obtained from L. Cheng (Johns Hopkins University, Baltimore, MD, USA), with verified normal karyotype and was contamination free. hiPSCs were maintained on Geltrex-coated plates (Thermo Fisher Scientific, A1413302) with TeSR-E8 medium (STEMCELL Technologies, 05940) in a 37C, 5% CO2 humidified incubator. Cells were passaged with ACCUTASE (STEMCELL Technologies, 07920) every 4 to 5 days at ~70% confluence, and autodifferentiated cells were marked and mechanically removed before passaging. We added 10 M Y-27632 (STEMCELL Technologies, 72304) into the TeSR-E8 medium on the first day after passaging.

The hiPSC line was induced to differentiate into ROs, as described previously (15). Briefly, on D0, hiPSCs were treated with dispase (STEMCELL Technologies, 07923) until the edges of the clones began to curl, after which they were scraped into small pieces and cultured in suspension with mTeSR1 medium (STEMCELL Technologies, 05850) and 10 M blebbistatin (Sigma-Aldrich, B0560) to induce aggregate formation. Aggregates were gradually transitioned into neural induction medium (NIM) containing Dulbeccos Modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F-12) (Thermo Fisher Scientific, 11330), 1% N2 supplement (Thermo Fisher Scientific, 17502), 1 MEM Non-Essential Amino Acids Solution (NEAA) (Thermo Fisher Scientific, 11140), heparin (2 g/ml; Sigma-Aldrich, H3149), and 1% antibiotic-antimycotic (Thermo Fisher Scientific, 15240) by replacing the medium with a 3:1 ratio of mTeSR1/NIM on D1, 1:1 on D2, and 100% NIM on D3. On D7, aggregates (average size of 250 50 m) were seeded onto Geltrex-coated dishes containing NIM at an approximate density of 10 aggregates/cm2 and switched to retinal differentiation medium (RDM) on D16 containing 70% Dulbeccos Modified Eagle Medium (DMEM) (Thermo Fisher Scientific, 11965) and 30% Hams F-12 Nutrient Mixture (F-12) (Thermo Fisher Scientific, 11765) supplemented with 2% B27 supplement (Thermo Fisher Scientific, 12587010), 1 NEAA, and 1% antibiotic-antimycotic. On D28, the neural retina domains were manually detached with a sharpened Tungsten needle under an inverted microscope and then collected and cultured in suspension in RDM. On D42, RDM was transitioned into retinal maturation medium (RMM) containing 60% DMEM, 25% F-12, supplemented with 10% FBS (Thermo Fisher Scientific), 100 M taurine (Sigma-Aldrich, T0625), 2% B27, 1 NEAA, 1 GlutaMAX supplement (Thermo Fisher Scientific, 35050), and 1% antibiotic-antimycotic. We freshly added 1 M retinoic acid (Sigma-Aldrich, R2625) to the RMM when the medium was changed twice a week.

Human retinae were fixed in 4% paraformaldehyde (PFA; Sigma-Aldrich, 16005) for 2 hours at RT, and ROs were fixed in 4% PFA for 30 min at RT. All samples were washed in DPBS (three times for 10 min), dehydrated with a sucrose gradient (15% for 30 min at RT and 30% overnight at 4C), and embedded in Tissue-Tek OCT Compound (Sakura, 4583) for freezing. Samples were sectioned (10 m unless otherwise stated), air dried for 1 hour, washed in DPBS (three times for 10 min), blocked in 10% bovine serum albumin (BSA; Sigma-Aldrich, B2064) in DPBS with 0.25% Triton X-100 (Sigma-Aldrich, T9284) for 1 hour at RT, and incubated with a primary antibody in 10% BSA in DPBS with 0.25% Triton X-100 at 4C overnight. The next day, slides were washed in DPBS (three times for 10 min) and incubated with corresponding species-specific Alexa Fluor 568 or Alexa Fluor 647conjugated secondary antibodies (1:500; Thermo Fisher Scientific, A-11036 and A-21245, respectively) in DPBS for 2 hours at RT. The slides were incubated in 4,6-diamidino-2-phenylindole (DAPI) (1:1000; Thermo Fisher Scientific, D1306) in DPBS for 5 min, washed in DPBS (three times for 10 min), and cover slipped. Primary antibodies against the following proteins were used at the indicated dilutions: GNAT1 (1:200; Santa Cruz Biotechnology, sc-389), RCVRN (1:100; Millipore, AB5585), and NR2E3 (1:100; R&D Systems, PP-H7223-00). Fluorescence images were acquired with an LSM 800 confocal microscope (Zeiss).

shRNA sequences of targeted genes (table S1) were synthesized by Tsingke Biological Technology and cloned into shRNA expression vector pAAV-U6-shRNA-CMV-mKate2-SV40, and pAAV-U6-shRLuc-CMV-mKate2-SV40 vector with luciferase shRNA (gtgcgttgctagtaccaacttcaagagagttggtactagcaacgcactttttt) was used as control. The complementary DNA (cDNA) of the CRX gene for overexpression was cloned into the pEF1-cDNA-IRES2-mKate2 vector, and the pEF1-IRES2-mKate2 vector without CRX cDNA was used as control. Primers used are listed in table S1. High-quality vectors were extracted using the NucleoBond Xtra Maxi EF Kit (Macherey-Nagel, 740424.50), with a final concentration of 1 g/l used for electroporation. In all experiments, electroporation was performed on both control and experimental groups. ROs for electroporation were manually cut into ~500-m (diameter) pieces under an inverted microscope, equally distributed to both control and experimental groups, and resuspended in the Human Stem Cell Nucleofector Kit 1 (Lonza, VPH-5012). Ten pulses of electroporation were performed on both sides of the small balls under the following parameters: square wave, 35 V, 1 Hz, and 5% duty.

Total RNA was isolated from samples with TRIzol (Thermo Fisher Scientific, 15596018) and converted into cDNA with a PrimeScript RT Master Mix (TaKaRa, RR036A). FastStart Essential DNA Green Master (Roche, 06924204001) was then used for qRT-PCR analysis, with RNA-seq performed on an Illumina HiSeqXten-PE150. Primer sequences for qRT-PCR are shown in table S1.

ATAC-seq was performed as described previously (11, 46). Briefly, a total of 50,000 cells were washed twice with 50 l of cold DPBS and resuspended in 50 l of lysis buffer [10 mM tris-HCl (pH 7.4), 10 mM NaCl, 3 mM MgCl2, and 0.1% (v/v) NP-40 substitute (Sigma-Aldrich, 11332473001)]. The suspension of nuclei was then centrifuged for 10 min at 500g at 4C, followed by the addition of 50 l of transposition reaction mix (10 l of 5 TTBL buffer, 4 l of TTE mix, and 36 l of nuclease-free H2O) of TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme Biotech, TD501). Samples were then incubated at 37C for 30 min. DNA was isolated using the QIAquick PCR Purification Kit (QIAGEN, 28106). ATAC-seq libraries were first subjected to five cycles of preamplification using NEBNext High-Fidelity 2X PCR Master Mix (New England Biolabs, M0541S). To determine the suitable number of cycles required for the second round of PCR, the library was assessed by qPCR as described previously (11) using NEBNext High-Fidelity 2X PCR Master Mix with SYBR Green I Nucleic Acid Gel Stain (Thermo Fisher Scientific, S7563) and then PCR amplified for the appropriate number of cycles. Libraries were purified with the QIAquick PCR Purification Kit. Library quality was checked using the High Sensitivity DNA Analysis Kit (Agilent, 5067-4626). Last, 2 150 paired-end sequencing was performed on an Illumina HiSeq X-10.

FASTQ files were evaluated for quality control using FastQC (v0.11.5) (www.bioinformatics.babraham.ac.uk/projects/fastqc/). Sequence alignment was performed using STAR (v2.5.2a) with reference assembly hg19. We estimated gene expression levels using reads per kilobase of transcript per million mapped reads (RPKM) values. DEGs were filtered by an RPKM value of >5 for one stage and an absolute value of log2 fold change >1 between any two groups. GO analysis was performed using David v6.8. The RNA-seq data of the developing human retina were obtained from the previous study (8), and we defined D52/D54, D57, D67, D80, D94, D105, D115, D125, D132, and D136 as GW7, GW8, GW10, GW11, GW13, GW15, GW16, GW18, GW19, and GW20.

Primary data were processed as described previously (19). In simple terms, we removed adapter sequences and then mapped reads to hg19 using Bowtie2. The PCR duplicates and chromosome M were removed. The uniquely mapped reads were shifted +4/5 base pair (bp) according to the strand of the read. All mapped reads were then extended to 50 bp centered through the cleavage position. Peak calling was performed using MACS2 with options - f BED -g hs, -q 0.01, --nomodel, --shift 0.

ATAC-seq data quality was comprehensively studied in the previous work (17). Briefly, we used several parameters to evaluate data quality, including number of raw reads, overall alignment rate, final mapped reads, final mapped rate, percentage of reads mapped to chromosome M, percentage of reads mapped to repeat regions (black list), percentage of reads filtered out by low MAPQ score, percentage of PCR duplicates, TSS enrichment score (reads enriched at 2 kb around TSS versus background), and read length distribution.

Peak calling was performed using MACS2 from all sample reads. The number of raw reads mapped to each peak at each condition was quantified using the intersectBed function in BedTools. Raw counts in peaks were normalized using the DESeq package in R. Peak intensity was defined as the log2 of the normalized counts. Samples were then grouped into 17 categories (30 samples; RO: w0, w2, w4, w6, w10, w15, w23, and w30; human retina: GW6, GW10, GW11, GW12, GW14, GW15, GW20, GW24, and GW25). First, to remove the genomic regions dominated by hiPSCs, we compared peaks between RO w0 and other time points (w2 to w30) to remove peaks with log2 fold change >1 on w0 and SD <1 on other time points. Significance analysis was then performed by pairwise comparison with eight categories of RO samples and nine categories of human retinal samples using DESeq with P < 0.01, false discovery rate (FDR) < 0.01, log2 fold change >1, and intrinsic analysis with z score >1. We lastly obtained 10,563 differential accessible peaks. We used the long-distance peaks (located 1 kb outside the TSS of the gene) to calculate the correlation between samples. Unsupervised clustering was performed using Cluster 3.0 and visualized in Treeview. GO and other enriched functions of cis-regulatory regions were performed with GREAT.

Intrinsic analysis followed the steps described in the previous research (10). We defined correlation matrix C, where Cp,q is the Pearson correlation between samples p and q where all peaks were included. Similarly, we defined correlation matrix Ci, where Cip,q is the Pearson correlation between samples p and q where all peaks except for peak i were excluded. We defined delta matrix, deltaCi = C Ci. We defined wbScorei = average (deltaCireplicates) average (deltaCinonreplicates). Replicates were defined as samples at the same time point, and nonreplicates otherwise. For peak i, the greater the wbScorei, the less variance the peak intensity was within the replicates and the greater variance within nonreplicates. We then calculated the average and SD of all wbScore (from I = 1 to N). We defined z score = (wbScorei average (wbScorei=1,N))/SD (wbScorei=1,N).

Details of protocols and standards for DHS-seq are described by ENCODE (www.encodeproject.org/). All replicates of DHS-seq samples were combined before analysis for the D74 (DHS-GW11) and D125 (DHS-GW18) time points. The Bowtie2 algorithm was implemented to align the reads to the human (hg19) reference genome (with option --very-sensitive). PCR duplicates, reads mapped to repeated regions, and chromosome M were removed.

To correlate the developmental stages between human retina and RO, we applied OE-DTW analysis (21). DTW is a popular technique for comparing time series. The rationale behind DTW is that given two time series, they should be stretched or compressed locally to make one resemble the other as much as possible. We used the R package DTW on expression profiles of human retinal development spanning from GW6 to GW25. The analysis was performed on the 3235 genes from the human RNA-seq data to find an optimal alignment between the human retinal and RO development.

The TF motif enrichment analysis was performed using HOMER with options: findmotifs.pl input.fa fasta output. To obtain genes that may be regulated by a certain TF, we overlapped all the binding site of TFs with the open sites. Genes with TF binding sites in the promoter region were then considered to be possible regulated genes.

For footprint, we adjusted the read start sites to represent the center of the transposons binding. Previous descriptions of the Tn5 transposase show that the transposon binds as a dimer and inserts two adaptors separated by 9 bp. Therefore, we modified the reads aligned file in the SAM format by offsetting +4 bp for all the reads aligned to the forward strand and 5 bp for all the reads aligned to the reverse strand. We then converted a shifted base SAM file to the BAM format and had the BAM file sorted using SAMtools. We overlaid TF binding sites with reads in each sample of the C4 and C5 peak regions. We then averaged the overlaid read counts of a 150-bp genomic region centered by the motif sites for motif footprints.

To study the regulatory mechanisms of TF NFIB, we predicted the potentiality of NFIB to bind to retinal-related genes. First, we selected a total of 35 genes enriched in the highlighted term in fig. S6A. We expanded each gene with the upstream of TSS by 10 kb and the downstream of gene transcription termination site by 5 kb. Next, we overlapped the binding site of NFIB in the peak regions of our ATAC-seq with extended gene regions. To better compare the possibility of these genes bonded by the NFIB motif, we calculated the flanking accessibility and the footprint depth of the motif binding regions. This is based on previous work (47). We first defined two key relative positions: (i) The footprint base is the region encompassing the very center of the motif and is defined as a motif binding site, and (ii) the footprint flank is the region immediately adjacent to the TF binding site and is defined as the region between the end of the footprint base and 100 bp away from the motif end. The accessibility of the motif region and the flank region was calculated. The higher value for footprint depth and the lower value for flanking accessibility indicate strong factor occupancy. We defined binding potential = flanking accessibility/footprint depth to characterize the binding potential of a gene region.

To map the regulatory network throughout the retinal developmental process, we selected human GW6, GW10, and GW20 and RO w6, w10, and w23 to represent the early, middle, and late stages of retinal development, respectively. According to Fig. 2A, we assigned motifs enriched in the C1 and C2 to the early stage and motifs enriched in C4 and C5 to the late stage. Because the development of ROs in the middle stage appeared to be slower than that of the human retina in C4, we assigned motifs enriched in C2 and C4 to the human middle stage and motifs enriched in C2 to the RO middle stage. First, we used HOMER to find the TFs that were bound to each cluster (P < 1 1020). A TF with a higher gene expression level on a time point than the average expression of all time points was considered as a member of the regulatory network of this time point, and then we constructed a transcriptional regulatory network. We defined the promoter region of TF-Y as going from the upstream 10 kb to the downstream 1 kb of TSS. If TF-X binds to the promoter of TF-Y, then we assumed that TF-X regulates TF-Y. The size of each node indicates the TF enrichment in that stage, and the color of each node indicates the TF expression in that stage. The correlation between TF-X and TF-Y expression (CX,Y) was calculated: CX,Y > 0.5, positive correlation; CX,Y < 0.5, negative correlation; 0.5 < CX,Y < 0.5, no correlation. We defined the connection score of each node in the network as its edge counts multiplied by the SD of its expression. To measure the extent of consistency between human retinae and ROs, we compared the similarities of their regulatory networks. We defined similarity score: S = 1 D (D = 0.5 N/M + 0.5 (I 0.5)/J), where D values represent differences between human retinae and ROs over the same time period. The differences in regulatory networks come from two aspects. One is that the two regulatory networks share some common TFs, so we used the ratio of the different connections (N) and all connections (M) in the same TF to represent this difference. The other is derived from the different TFs. We divided half the number of different TFs (I) by the number of all TFs (J). We assumed that they may share the same contribution to differences in regulatory networks; therefore, we multiplied the respective coefficients by 0.5.

DHS-seq data for mouse retinae (E14.5, P1, and P7) from ENCODE (www.encodeproject.org/) were analyzed. The Bowtie2 algorithm was implemented to align the reads to the mouse (mm9) reference genome (with option --very-sensitive). PCR duplicates, reads mapped to repeated regions, and chromosome M were removed. After peak calling and DESeq normalization, significance analysis was then performed on adjacent time points with P < 0.01, FDR < 0.01, log2 fold change >2. We lastly obtained 8967 differential peaks. Unsupervised clustering was performed using Cluster 3.0 and visualized in Treeview. GO and other enriched functions of cis-regulatory regions were performed with GREAT. To identify chromatin states, we used the ChromHMM software (v.1.06) according to the previous paper (48). Neighborhood enrichment command was used to calculate the enrichment of different chromatin states in cluster peak regions.

We calculated the signals of H3K4me3 and H3K27me3 modifications in each peak of C4 at GW13 and GW14. We defined average signals of a modification (m) in one peak region (g) as S (mg). If S (mg) > 1, then the peak region g enriched modification m. We divided the peaks of C4 into two subgroups, namely, H3K4me3-only subgroup and bivalent subgroup according to the enrichment of different histone modifications in peak region. If a peak region simultaneously enriched with both modifications of H3K4me3 and H3K27me3, then the peak is in a bivalent state, and if enriched with the H3K4me3 but not H3K27me3 modification, then the peak is H3K4me3-only state.

We extracted the fluorescence intensity of RCVRN by ImageJ software, following the ImageJ User Guide. Corrected total cell fluorescence (CTCF) of each calculated cell (mKate2+ cells and mKate2-RCVRN+ cells) in the same slice was compared with the mean CTCF of mKate2-RCVRN+ cells to normalize the CTCF between different slices. The normalized CTCF of mKate2+ cells in both the control and NFIB_KD groups was compared with the mean of the normalized CTCF of mKate2+ cells in the control group, and then the relative intensity of the RCVRN in each cell was obtained.

Statistical significance was analyzed with unpaired two-tailed t tests or one-way analysis of variance (ANOVA). A value of P < 0.05 was considered statistically significant. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. Data are presented as means SEM as indicated in the figure legends. All statistical analyses were performed in GraphPad Prism v7.00.

Read the rest here:
Chromatin accessibility analysis reveals regulatory dynamics of developing human retina and hiPSC-derived retinal organoids - Science Advances

The NLRP3 receptor protein is responsible for detecting potential pathogens in the body and launching an immune response. (Image by MLGProGamer123 via Wikimedia Commons)

Chronic inflammation, which results when old age, stress or environmental toxins keep the bodys immune system in overdrive, can contribute to a variety of devastating diseases, from Alzheimers and Parkinsons to diabetes and cancer.

Now, scientists at the University of California, Berkeley, have identified a molecular switch that controls the immune machinery responsible for chronic inflammation in the body. The finding, which appears online Feb. 6 in the journal Cell Metabolism, could lead to new ways to halt or even reverse many of these age-related conditions.

My lab is very interested in understanding the reversibility of aging, said senior author Danica Chen, associate professor of metabolic biology, nutritional sciences and toxicology at UC Berkeley. In the past, we showed that aged stem cells can be rejuvenated. Now, we are asking: to what extent can aging be reversed? And we are doing that by looking at physiological conditions, like inflammation and insulin resistance, that have been associated with aging-related degeneration and diseases.

In the study, Chen and her team show that a bulky collection of immune proteins called the NLRP3 inflammasome responsible for sensing potential threats to the body and launching an inflammation response can be essentially switched off by removing a small bit of molecular matter in a process called deacetylation.

Overactivation of the NLRP3 inflammasome has been linked to a variety of chronic conditions, including multiple sclerosis, cancer, diabetes and dementia. Chens results suggest that drugs targeted toward deacetylating, or switching off, this NLRP3 inflammasome might help prevent or treat these conditions and possibly age-related degeneration in general.

This acetylation can serve as a switch, Chen said. So, when it is acetylated, this inflammasome is on. When it is deacetylated, the inflammasome is off.

By studying mice and immune cells called macrophages, the team found that a protein called SIRT2 is responsible for deacetylating the NLRP3 inflammasome. Mice that were bred with a genetic mutation that prevented them from producing SIRT2 showed more signs of inflammation at the ripe old age of two than their normal counterparts. These mice also exhibited higher insulin resistance, a condition associated with type 2 diabetes and metabolic syndrome.

The team also studied older mice whose immune systems had been destroyed with radiation and then reconstituted with blood stem cells that produced either the deacetylated or the acetylated version of the NLRP3 inflammasome. Those who were given the deacetylated, or off, version of the inflammasome had improved insulin resistance after six weeks, indicating that switching off this immune machinery might actually reverse the course of metabolic disease.

I think this finding has very important implications in treating major human chronic diseases, Chen said. Its also a timely question to ask, because in the past year, many promising Alzheimers disease trials ended in failure. One possible explanation is that treatment starts too late, and it has gone to the point of no return. So, I think its more urgent than ever to understand the reversibility of aging-related conditions and use that knowledge to aid a drug development for aging-related diseases.

Co-authors of the study include Ming He, Hou-Hsien Chiang and Hanzhi Luo, previously at UC Berkeley where the research was carried out; Zhifang Zheng, Mingdian Tan, Rika Ohkubo and Wei-Chieh Mu at UC Berkeley; Qi Qiao, Li Wang and Hao Wu at Harvard Medical School; and Shimin Zhao at Fudan University.

This research was supported in part by the National Institutes of Health under grants R01DK117481, R01DK101885, R01AG063404, R01AG 063389, DP1HD087988 and R01Al124491; the National Institute of Food and Agriculture; the France-Berkeley Fund, a Glenn/AFAR Scholarship; the Dr. and Mrs. James C.Y. Soong Fellowship; the Government Scholarship for Study Abroad (GSSA) from Taiwan; the ITO Foundation Scholarship and the Honjo International Scholarship.

RELATED INFORMATION

Originally posted here:
Molecular 'switch' reverses chronic inflammation and aging - UC Berkeley

Eric Stegers heart is full, although his liver is smaller by 60%.

Steger, a 50-year-old man from Sunnydale, California, affiliated with Chabad, was in Pittsburgh earlier this month fulfilling his dream of donating an entire lobe of his liver to help save the life of another.

The liver recipient, Conservative Rabbi Jeffrey Kurtz-Lendner, 53, said he feels like he has been given a second chance at life.

Get The Jewish Chronicle Weekly Edition by email and never miss our top storiesFree Sign Up

Kurtz-Lendner, who relocated to Pittsburgh from Iowa for the purpose of obtaining a transplant at UPMC, had been diagnosed with fatty liver cirrhosis, but the doctors did not know how serious it was until they were in the midst of the transplant.

I could have died before I got put onto a list, said Kurtz-Lendner, who, after the Jan. 7 surgery, is still recuperating but has been discharged from the hospital.

Steger, a math tutor at Foothill College in Northern California, has donated stem cells for a bone marrow transplant and platelets many times, and has been wanting to help save a life with one of his organs for years. He even traveled to Israel to donate a kidney, but was ultimately turned down because he had hypertension.

About a year ago, though, he saw a UPMC commercial airing in California that advertised the fact that it was now performing altruistic liver donations.

I decided to give it a try, said Steger.

He then got in touch with Chaya Lipschutz, an Orthodox woman from Brooklyn who donated a kidney to a stranger in 2005, and since then has made it her work to help others find kidney matches. She receives no money for her services.

Lipschutz had made the shidduch with the kidney patient in Israel for Steger that did not work out, he said.

As fate would have it, Lipschutz did know people who needed a live liver transplant. Steger was medically cleared for the procedure, but the first few people with whom he matched found other donors. Lipschutz then turned to message boards to post that she had an able and willing donor.

Now I was a solution in search of a problem, said Steger.

When Kurtz-Lendners sister in Teaneck, New Jersey, happened to see Lipschutzs post, the match was made.

Post-surgery, both donor and recipient are doing well.

Im feeling very positive, said Kurtz-Lendner, noting that full recovery from the procedure will take about a year. Two weeks ago, I was dying. Now, I have another 30 years.

He, his wife Robin, and his oldest daughter will remain in Pittsburgh for at least six months.

Kurtz-Lendner did not meet Steger until after the surgery, and sees him as an inspiration of a human being. I appreciate what he has done. He just saved my life.

Steger returned to California this week. During his time in Pittsburgh, he received warm hospitality from the citys Jewish community, particularly the Bikur Cholim of Pittsburgh, run by Nina Butler, he said.

Patients and families who come here from out of town always remind us of how special our community is, said Butler. As the Bikur Cholim of Pittsburgh, Im simply organizing the generosity of volunteers to provide the specific support that each patient wants. That started before Jeff or Eric arrived, answering their questions about housing, Shabbat observance and kosher food.

Eric is observant and came unaccompanied, so his housing was complicated because the Family House does not allow patients to stay completely alone, Butler explained. We provided home hospitality, and we also organized volunteers to drop off meals for Eric while his hosts were at work. Most of all, we formed relationships with both patients and Jeffs family so they knew there were Pittsburghers who had their backs.

Robin Kurtz-Lendner said that she and her husband felt so supported, even before we got here. Its been incredible. The whole community has been rallying around us and its really been appreciated.

Donating part of his liver was not easy, Steger acknowledged. Still, he wants to encourage others to consider organ donation.

Im not going to sugarcoat it, he said. It was the hardest thing Ive ever done. It was a year out of my life, one full year when I was thinking about this all the time.

There was a battery of tests, the surgery itself, and now the recovery phase, he said, which all carry physical and emotional risks.

But he is hoping what he did will help generate continued interest in organ donation.

I hope my experience will inspire other people to investigate it for themselves, he said.pjc

Toby Tabachnick can be reached atttabachnick@pittsburghjewishchronicle.org.

Follow this link:
California man donates part of his liver to Conservative rabbi in Pittsburgh - The Australian Jewish News

For centuries, stories have been told of people whose hair turned prematurely white from harrowing stress. Now, Harvard researchers have found a scientific explanation.

"Marie Antoinette syndrome" is the term commonly used to for the rapid, premature graying, because legend has it that the French queen's hair turned white the night before she faced the guillotine.

Mice get "Marie Antoinette syndrome" when they're highly stressed, too, so Harvard researchers studied them to figure out how stress can induce a permanent loss of hair pigment.

"We started by thinking maybe the immune system is involved," says Harvard stem cell scientist Ya-Chieh Hsu. The hypothesis was that under stress, the immune system attacks the stem cells that generate hair pigment cells.

But when the researchers tested it in mice with defective immune systems that couldn't attack, "They still got gray hairs under stress so that's incorrect," Hsu says.

Next hypothesis: that the stress hormone cortisol was killing the pigment stem cells. The research team tried removing the adrenal glands that make cortisol, but the mice still developed gray hair.

"So we know that cortisol is not involved," Hsu says.

Finally, the research team focused on the sympathetic nervous system the network of nerves best known for the "fight-or-flight" response to danger. Hsu says it just didn't seem like a likely candidate, even though it gets activated by stress, because the fight-or-flight response is temporary.

But now it's clear that "a very transient fight-or flight response can lead to permanent changes in stem cells," she says. "That is a much bigger effect than what we would initially anticipate."

The research finds that during stress, the sympathetic nervous system over-activates and so depletes the stem cells that make pigment cells. No more pigment cells no more hair color.

The paper is just out in the journal Nature.

William Lowry, a biology professor at the University of California, Los Angeles who studies hair follicles, says we've long known there's a connection between stress and graying hair, but not what it was.

"This paper really nails that, in the sense of figuring out what different types of systems in your body come together" to produce the effect, he says.

And that mechanism could apply to more than hair, Lowry says.

"Is this happening in different organs? Is this the canary in the coal mine?" he asks. "I think sure. There's no reason to think that this is a one-off."

Ya-Chieh Hsu at Harvard says the hope is that understanding how stress harms stem cells could lead to ways to block that harm.

Also --- it's not clear whether the stress mechanism that turns hair white is the same as the normal graying that comes with age, but if it is, there could be a way to block that, too.

Go here to see the original:
How Stress Turns Hair White: Harvard Study Points To 'Fight-Or-Flight' Response - WBUR

PHOTO COURTESY OF ROANE STATE COMMUNITY COLLEGE, TN: Typical nervous tissue that can now be grown as organoids in the lab.

Bio Bites

By R. Gary Raham

One of the big scientific news stories of 2019 involved the use of organoids to help fight disease, and to learn more about how embryos build entire human beings from one fertilized egg cell. The term organoids has a science fictiony sound to it. A title like Attack of the organoids wouldnt be out of place in an SF library. Actually, the ability to create specialized tissuelike bundles of brain neurons that hook together to transmit nerve impulsescan raise a few hairs on ones neck. But organoids do hold great promise for curing diseases, broadening our understanding of development, and personalizing medical treatments.

Stem cells allow scientists to build organoids. Stem cells are like major subcontractors produced by embryos to build the various organs and organ systems we depend on. These pluripotent cells (cells that can differentiate in many ways) can produce brain, kidney, lung, intestinal, stomach, and liver tissue. The tissue clumps produced tend to be smallroughly the size of a peapartly because they dont have access to the circulatory system the body uses to provide oxygen and nutrients and remove wastes. Scientists have to provide work-arounds to keep organoids alive and functioning.

One of the amazing things about organoids is that they self-organize into recognizable tissues without input from an entire body. Take brain cells for example. The neurons produced by stem cells link up and form networks that are capable of transmitting nerve impulses like an intact, complete brain. One leading researcher in this field of study is Alysson Muotri, a biologist at University of California San Diego School of Medicine. His website is http://www.medschool.ucsd.edu. He also has a fascinating series of YouTube videos called Building The Brain With Alysson Muotri. Muotri was senior author on a paper in 2019 in Cell Stem Cell. His lab was able to nurture the growth of brain organoids for many months. After four months electrical activity in the organoids began to increase exponentially. By twenty-five weeks, a computer program had a hard time distinguishing between brain wave patterns produced by organoids and pre-term babies.

Brain tissue organoids also hold promise for studying conditions like autism in human beingsa kind of neurological condition marked by differences in learning styles, repetitive motions, and sometimes difficulty with language and communication. The Harvard Stem Cell Institute is also studying how the Zika virus associates with microcephaly (small brain syndrome) during early embryo development.

Someday, scientists may be able to routinely take stem cells from individuals and test the efficacy of drugs on that persons liver cells, for example, to make sure those drugs wont produce harmful or fatal effects.

The brave new world of organoids is comingand not just in the next SF novel you read.

Here is the original post:
The Brave New World of Organoids - North Forty News

Irving Weissman and Joseph McCune, Opinion contributors Published 7:00 a.m. ET Jan. 24, 2020

Severe Trump administration restrictions mean millions of Americans of all political and religious stripes won't benefit from fetal tissue research.

Last summer the Trump administration curtailed federal funding of medical research using human fetal tissue; the new rulestook effect Oct. 1. More recently, the administration addedrestrictions that are even more severe.

Immediately, important work at two NIH-supported labs in Montana and California that are fighting the AIDS epidemic stopped because they were testing new medications against HIV using mice with human immune systems derived from human fetal tissue. In the near term, all National Institutes of Health (NIH) funding of research using fetal tissuewill likely cease.

More than 30years ago, we invented SCID-hu mice for biomedical research on diseases affecting humans, by implanting human fetal blood-forming and immune system tissuesinto mice whose immune systems had been silenced. The implanted immune tissues came from an aborted fetus, and allowed our otherwise immune-deficient mice to exist and be vulnerable to viruses that infect humans.

Tissues from living infants would not have worked;they are too far along in development and nearly impossible to obtain. This mouse model (and later versions of it) became the only living system, outside of a human, in which advanced therapies for diseases like AIDS and other viral infections could be evaluated before they were given to people.

Our work with human fetal tissue proceeded with the highest level of caution and vigilance. We received advice from bioethicists, clergyand government officials, which led to the establishment of strict guidelines that are still used today. No woman was asked or paid to terminate a pregnancy, the termination process was unaltered, and the women were asked for donation of the organs only after they had decided to terminate the pregnancy. Thus, obtaining the fetal tissue for medical research had no impact on ending pregnancies.

Since then, mice with transplanted human fetal tissues have been successfully used by scientists to identify blood stem cells and to devise treatments now availableor in clinical trialsfor cancer, various viral infections, Alzheimers disease, spinal cord injuries, and other diseases of the nervous system. Such diseases kill or cripple many Americans including pregnant women, fetusesand newborn infants. Many of them have only a short window of opportunity wherein a new therapy can treat them, and a delay can be fatal.

National Institutes of Health in Bethesda, Maryland, on Oct. 21, 2013.(Photo: *, Kyodo)

The Trump administration's new rules are tantamount to a funding ban. In academic labs, the experiments are done by students and fellows in training, and the new rules block any NIH-funded students or fellows from working with human fetal tissue. Those who imposed the banmust bear responsibility for the consequences: People will suffer and die for lack of adequate treatments.

Americans pay the price:Trump administration's 'scientific oppression' threatens US safety and innovation

At a December 2018 meeting at NIH,after hearing scientific evidence about alternative research methods such as the use of adult cells, experts concluded that the use of fetal tissue is uniquely valuable. Nonetheless, the administration severely restricted the use of fetal tissue, thereby denying millions of Americans the fruits of such research Americans of all political stripes, since deadly viruses and cancers do not care who you vote for.

These restrictions subvert the NIH mission, which is to advance medicine and protect the nations health. To the extent that it was motivated by the religious beliefs of those in charge, it bluntly transgresses the American principle of separation of church and state. As a result, both believers and non-believers will die.

Of course, all who take the Hippocratic Oathto "do no harm,"which includes all medical doctors, will always offer and deliver all types of therapies that are available.

Restricting science: Trump EPA's cynical 'transparency' ploy would set back pollution science and public health

However, we believe that thoseresponsible forthis de facto ban, and perhapsthose who agree with them, should personally accept its consequences. We challenge them tobe true to their beliefs. They should pledge to never accept any cancer therapy, any AIDS medication, any cardiac drug, any lung disease treatment, any Alzheimers therapy, or any other medical advance that was developed using fetal tissue including our mice. Its a long list, one that you can learn about from us here. Should this apply to you, be faithful and be bold: Take the pledge.

Irving Weissman is a Professor of Pathology and Developmental Biology and the Director of the Stanford Institute of Stem Cell Biology and Regenerative Medicine and Ludwig Center for Cancer Stem Cell at Stanford University School of Medicine. Joseph McCune is Professor Emeritus of Medicine from the Division of Experimental Medicine at the University of California, San Francisco. The views expressed here are solely their own.

Autoplay

Show Thumbnails

Show Captions

Read or Share this story: https://www.usatoday.com/story/opinion/2020/01/24/trump-fetal-tissue-research-ban-hurts-all-americans-column/4553379002/

Excerpt from:
If you want to ban fetal tissue research, sign a pledge to refuse its benefits - USA TODAY

SAN DIEGO, CA, Jan. 02, 2020 (GLOBE NEWSWIRE) -- via NEWMEDIAWIRE --Diomics Corporation, a leader in forensic, diagnostic, and therapeutic science since 2009, and the laboratory of Dr. Jonathan Lakey, Professor of Surgery and BiomedicalResearchand Director of the Clinical Islet Program at the University of California, Irvine (UCI), today announced a Sponsored Research Agreement to ultimately improve islet transplantation for patients living with type 1 diabetes.

The current method for islet transplantation requires invasive, difficult, and time consuming surgeries that create stress and risk for both the patients and the islets. To circumvent these issues, cell encapsulation has been proposed as the next treatment option. Biomaterials can protect the transplanted islets from destruction from the body. Polycaprolactone (PCL) polymer has been used in cell replacement therapy, however, the PCL polymer degrade too slowly and exhibit poor cell adhesion qualities for optimal cell replacement therapy. Diomics technology overcomes these issues for improved cell adhesion.

Leading the Diomics Sponsored Research Agreementresearch at UCI is Dr. Jonathan Lakey, a world-class subject matter expert on cell therapies including pancreatic islets and stem cells. Dr. Lakey has pioneered the development of novel methods for implantation of pancreatic islets for patients with diabetes. I am thrilled for the opportunity to work with Diomics and examine this novel and important proprietary biomaterial, said Dr Lakey. I am most excited about the potential variety of applications for this novel material.

Diomics recently filed provisional patents with claims broadly covering its proprietary polymer technology, Diomat, for applications in cell therapy, transdermal and related drug delivery methods. The Diomics and UCI research will support the development of key data that can be leveraged in clinical trials for improved islet transplantation therapy. Improved islet transplantation can restore natural insulin production for type 1 diabetes patients.

In this sponsored research project, Diomat foams will be used to characterize the Diomics material and examine encapsulated pancreatic islets and stem cells for improved islet transplantation therapy. This data will provide the key results to proceed with clinical trials using Diomat foam-encapsulated products.

Diomics is committed to providing innovative solutions through its materials and technologies that will lead the way to remarkable life science discoveries, said Diomics Chairman of the Board, Kirk Avery. We are honored to collaborate with Dr. Lakey and UCI.

ABOUT DIOMICS CORPORATION

Diomics Corporation creates highly efficient hydrophilic materials, based on patented Diomat technology, that improve the speed, sensitivity, and accuracy in the capture and detection of nucleic acids, proteins, and similar compounds. Our technology has broad applicability in a multitude of nanoscale settings in biomedical engineering, genomics, proteomics, and stem cell research. Diomics has filed a total of 20 patents and has 12 issued patents. For more information, visit:www.Diomics.com

ABOUT DR. LAKEY AT UCI

Dr. Jonathan Lakey is Professor of Surgery and Biomedical Engineering at the University of California, Irvine, and a world-class subject matter expert on cell therapies including pancreatic islets and stem cells. Dr. Lakey has over 395 publications and authored 45 book chapters and has pioneered the development of novel methods for implantation of pancreatic islets for patients with diabetes.

Diomics Contact:

Eric J. Mathur, CEO

Diomics Corporation

cell: 760.889.8929

emathur@Diomics.com

http://www.Diomics.com

Investor Relations Contact:

Jeff Ramson, Founder & CEO

PCG Advisory, Inc.

phone: 646-863-6893

jramson@pcgadvisory.com

http://www.pcgadvisory.com

Read the original:
Diomics Corporation and University of California, Irvine Collaborate to Enable Cell Therapy Clinical Trial for Type 1 Diabetes - BioSpace

For its promising investigational therapeutic approach to neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), BrainStorm Cell Therapeutics is theBuzz of BIO 2020 winnerin the Public Therapeutic Biotech category.

The Buzz of BIO contest identifies U.S. companies with groundbreaking, early-stage potential to improve lives. The event also is anopportunity to make investor connections that could take products to the next phase.

Ten biotechnology companies are nominated in each of the three categories ofBuzz of BIO: Public Therapeutic Biotech, Private Therapeutic Biotech, and Diagnostics and Beyond. In the Public Therapeutic Biotech category that BrainStorm won, nominated companies must be actively developing a publicly traded human treatment intended for review by theU.S. Food and Drug Administration (FDA).

As a developer of autologous cellular therapies treatments that use a patients own cells and tissues for debilitating neurodegenerative diseases, BrainStorm is now testing its NurOwn therapy for safety and effectiveness. The treatment involves extracting, from human bone, marrow-derived mesenchymal stem cells (MSCs), which are capable of differentiating into other cell types. The MSCs are then matured into a specific cell type that produces neurotrophic factors compounds that promote nervous tissue growth and survival. They are then reintroduced to the body via injection into muscles and/or the spinal canal.

Backed by a California Institute for Regenerative Medicine grant, Brainstorm has fully enrolledits randomized, double-blind, placebo-controlled Phase 3 clinical trial (NCT03280056) at six U.S. sites in California, Massachusetts, and Minnesota. Some 200 ALS patients are participating. A secondary safety analysis by the trials independent Data Safety Monitoring Board (DSMB) revealed no new concerns. Every two months, study subjects will be given three injections into the spinal canal of either NurOwn or placebo.

The trial is expected to conclude late this year. Results will be announced shortly afterward.

In a Phase 2 study (NCT02017912), which included individuals with rapidly progressing ALS, NurOwn demonstrated a positive safety profile as well as prospective efficacy.

The use of autologous MSC cells to potentially treat ALS was given orphan drug status by both the FDA and the European Medicines Agency.

Thanks to everyone who voted for BrainStorm during the Buzz of BIO competition,Chaim Lebovits, BrainStorm president and CEO, said in a press release. The entire management team at BrainStorm was very pleased with the results of this competition, and we look forward to presenting to an audience of accredited investors who may benefit from the companys story. We thank the BIO[Biotechnology Innovation Organization] team for singling out BrainStorms NurOwn as a key technology with the potential to improve lives.

As a contest winner, BrainStorm is invited to givea presentation at theBio CEO & Investor Conference, to be held Feb. 1011 in New York City, along with exposure to multiple industry elites and potential investors.

NurOwn cells also are being tested in a Phase 2 clinical study (NCT03799718) in patients with progressive multiple sclerosis.

Mary M. Chapman began her professional career at United Press International, running both print and broadcast desks. She then became a Michigan correspondent for what is now Bloomberg BNA, where she mainly covered the automotive industry plus legal, tax and regulatory issues. A member of the Automotive Press Association and one of a relatively small number of women on the car beat, Chapman has discussed the automotive industry multiple times of National Public Radio, and in 2014 was selected as an honorary judge at the prestigious Cobble Beach Concours dElegance. She has written for numerous national outlets including Time, People, Al-Jazeera America, Fortune, Daily Beast, MSN.com, Newsweek, The Detroit News and Detroit Free Press. The winner of the Society of Professional Journalists award for outstanding reporting, Chapman has had dozens of articles in The New York Times, including two on the coveted front page. She has completed a manuscript about centenarian car enthusiast Margaret Dunning, titled Belle of the Concours.

Total Posts: 6

Ins holds a PhD in Biomedical Sciences from the University of Lisbon, Portugal, where she specialized in blood vessel biology, blood stem cells, and cancer. Before that, she studied Cell and Molecular Biology at Universidade Nova de Lisboa and worked as a research fellow at Faculdade de Cincias e Tecnologias and Instituto Gulbenkian de Cincia. Ins currently works as a Managing Science Editor, striving to deliver the latest scientific advances to patient communities in a clear and accurate manner.

Originally posted here:
BrainStorm Cell Therapeutics Wins 2020 'Buzz of BIO' Award for ALS Investigational Therapy - ALS News Today