Molecular Omics

Earth tilted rotation and translation around the Sun produce one of the most pervasive periodic environmental signals on our planet giving rise to seasonal variations in diel cycles. Although marine phytoplankton plays a key role on ecosystems and present promising biotechnological applications, multiomics integrative analysis of their response to these rhythms remains largely unexplored. We have chosen the marine picoeukaryote Ostreococcus tauri as model organism grown under summer long days, winter short days, constant light and constant dark conditions to characterize these responses in marine phytoplankton. Although 80% of the transcriptome present diel rhythmicity under both seasonal conditions less than 5% maintained oscillations under all constant conditions. A drastic reduction in protein abundance rhythmicity was observed with 55% of the proteome oscillating. Seasonally specific rhythms were found in key physiological processes such as cell cycle progression, photosynthetic efficiency, carotenoid content, starch accumulation and nitrogen assimilation. A global orchestration between transcriptome, proteome and physiological dynamics was observed with specific seasonal temporal offsets between transcript, protein and physiological peaks.

The liver has a remarkable capacity to regenerate and thus compensates for repeated injuries through toxic chemicals, drugs, alcohol or malnutrition for decades. However, largely unknown is how and when alterations in the liver occur due to tolerable damaging insults. To that end, we induced repeated liver injuries over ten weeks in a mouse model injecting carbon tetrachloride (CCl4) twice a week. We lost 10% of the study animals within the first six weeks, which was accompanied by a steady deposition of extracellular matrix (ECM) regardless of metabolic activity of the liver. From week six onwards, all mice survived, and in these mice ECM deposition was rather reduced, suggesting ECM remodeling as a liver response contributing to better coping with repeated injuries. The data of time-resolved paired transcriptome and proteome profiling of 18 mice was subjected to multi-level network inference, using Knowledge guided Multi-Omics Network inference (KiMONo), identified multi-level key markers exclusively associated with the injury-tolerant liver response. Interestingly, pathways of cancer and inflammation were lighting up and were validated using independent data sets compiled of 1034 samples from publicly available human cohorts. A yet undescribed link to lipid metabolism in this damage-tolerant phase was identified. Immunostaining revealed an unexpected accumulation of small lipid droplets (microvesicular steatosis) in parallel to a recovery of catabolic processes of the liver to pre-injury levels. Further, mild inflammation was experimentally validated. Taken together, we identified week six as a critical time point to switch the liver response program from an acute response that fosters ECM accumulation to a tolerant "survival" phase with pronounced deposition of small lipid droplets in hepatocytes potentially protecting against the repetitive injury with toxic chemicals. Our data suggest that microsteatosis formation plus a mild inflammatory state represent biomarkers and probably functional liver requirements to resist chronic damage. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=163 HEIGHT=200 SRC="FIGDIR/small/476054v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@11ecc7aorg.highwire.dtl.DTLVardef@1027df5org.highwire.dtl.DTLVardef@9ba0f7org.highwire.dtl.DTLVardef@164f80a_HPS_FORMAT_FIGEXP M_FIG C_FIG The datasets generated via transcriptomics, proteomics as well as blood, histopathological and biochemical analysis were analyzed in an independent and integrative manner. The independent analysis was performed via state-of-the-art statistical approaches i.e. differential and consistently regulated genes and proteins. Combining the results identified three fibrosis phases. Using the KiMONo algorithm, a fibrosis specific multi-omic network was inferred. Within this network we identified several nodes connecting phase III specific features forming 13 distinct multi-omic modules suggesting a tolerance scheme. Some of these modules were experimentally validated and compared to 11 independent human studies of various liver diseases.

Embryonic stem cells (ESCs) have a unique ability to remain pluripotent while undergoing rapid rounds of cell division required for self-renewal. However, it is not known how cell cycle and pluripotency regulatory networks co-operate in ESCs. Here, we used stable isotope labeling with amino acids in cell culture (SILAC) combined with mass spectrometry to determine pluripotency proteome dynamics during cell cycle in mouse ESCs. We found the S/G2M-fluctuating pluripotency transcription factors (ESRRB, REST), chromatin regulators (JARID2, TRIM24) and proteins with E3 ligase activity (NEDD4L, PIAS2) to peak in S phase. This expression balance was disrupted upon inhibition of cyclin-dependent kinase 1 (CDK1) activity resulting in the shift of the expression peak from S to G2M. Our results demonstrate that mouse ESCs require CDK1 activity to maintain high S to G2M ratio of pluripotency regulators revealing critical role of cell cycle dynamics in balancing ESC identity.

Almost every organ consists of many cell types, each with its unique functions. Proteomes of these cell types are thus unique too. But it is reasonable to assume that interactome (inter and intra molecular interactions of proteins) are also distinct since protein interactions are what ultimately carry out the function. Podocytes and tubules are two cell types within kidney with vastly different functions: podocytes envelop the blood vessels in the glomerulus and act as filters while tubules are located downstream of the glomerulus and are responsible for reabsorption of important nutrients. It has been long known that for tubules mitochondria plays an important role as they require a lot of energy to carry out their functions. In podocytes, however, it has been assumed that mitochondria might not matter as much in both normal physiology and pathology1. Here we have applied quantitative cross-linking mass spectrometry to compare mitochondrial interactomes of tubules and podocytes using a transgenic mitochondrial tagging strategy to immunoprecipitate cell-specific mitochondria directly from whole kidney. We have uncovered that mitochondrial proteomes of these cell types are quite similar, although still showing unique features that correspond to known functions, such as high energy production through TCA cycle in tubules and requirements for detoxification in podocytes which are on the frontline of filtration where they encounter toxic compounds and therefore, as a non-renewing cell type they must have ways to protect themselves from cellular toxicity. But we gained much deeper insight with the interactomics data. We were able to find pathways differentially regulated in podocytes and tubules based on changing cross-link levels and not just protein levels. Among these pathways are betaine metabolism, lysine degradation, and many others. We have also demonstrated how quantitative interactomics could be used to detect different activity levels of an enzyme even when protein abundances of it are the same between cell types. We have validated this finding with an orthogonal activity assay. Overall, this work presents a new view of mitochondrial biology for two important, but functionally distinct, cell types within the mouse kidney showing both similarities and unique features. This data can continue to be explored to find new aspects of mitochondrial biology, especially in podocytes, where mitochondria has been understudied. In the future this methodology can also be applied to other organs to uncover differences in the function of cell types.

Induced pluripotent stem cell (iPSC)-derived neurons have emerged as a powerful model to investigate both neuronal development and neurodegenerative diseases. Although transcriptomics and imaging have been applied to characterize neuronal development signatures, comprehensive datasets of protein and post-translational modifications (PTMs) are not readily available. Here, we applied quantitative proteomics and phosphoproteomics to profile the differentiation of the KOLF2.1J iPSC line, the first reference line of the iPSC Neurodegenerative Disease Initiative (iNDI) project. We developed an automated workflow enabling high-coverage enrichment of proteins and phosphoproteins. Our results revealed molecular signatures across proteomic and phosphoproteomic landscapes during differentiation of iPSC-derived neurons. Proteomic data highlighted distinct changes in mitochondrial pathways throughout the course of differentiation, while phosphoproteomics revealed specific regulatory dynamics in GTPase signaling pathways and microtubule proteins. Additionally, phosphosite dynamics exhibited discordant trends compared to protein expression, particularly in processes related to axon functions and RNA transport. Furthermore, we mapped the kinase dynamic changes that are critical for neuronal development and maturation. We developed an interactive Web app (https://niacard.shinyapps.io/Phosphoproteome/) to visualize temporal landscape dynamics of protein and phosphosite expression. By establishing baselines of proteomic and phosphoproteomic profiles for neuronal differentiation, this dataset offers a valuable resource for future research into neuronal development and neurodegenerative diseases using this reference iPSC line. HighlightsO_LITemporal dynamics of proteome and phosphoproteome profiles in KOLF2.1J iPSC derived neurons. C_LIO_LIPhosphoproteomics highlights GTPase signaling and microtubule regulation in neuronal differentiation. C_LIO_LIKinome mapping reveals a shift in kinase activity patterns from early to late differentiation. C_LIO_LIShinyapp for visualizing the trajectory of protein and phosphosite expression during neuronal differentiation. C_LI

The experience of adversity in childhood can have life-long consequences on health outcomes. In search of mediators of this relationship, alterations of bio-behavioral and cellular regulatory systems came into focus, including those dealing with basic gene regulatory processes. Systems biology oriented approaches have been proposed to gain a more comprehensive understanding of the complex multiple interrelations between and within layers of analysis. We used co-expression based, supervised and unsupervised single and multi-omics system approaches to investigate the influence of childhood adversity on gene expression, protein expression and DNA methylation in CD14+ monocytes of healthy adults before and after exposure to an experimental psychosocial stress protocol. Childhood adversity explained some variance at the single analyte level and within gene and protein co-expression structures. A single-omic, post stress gene expression model differentiated best between participants with a history of childhood adversity and controls in supervised analyses. In unsupervised analyses, a multi-omics based model showed best performance but separated participants based on sex only. Multi-omics analyses are a promising concept but might yield different results based on the specific approach taken and the omic-datasets supplied. Here, stress associated gene-expression pattern were most strongly associated with childhood adversity, and integrating multiple cellular layers did not results in better discriminatory performance. Currently, the capacity and yield of different omics-profiling methods might limit the full potential of integrative approaches.

Ocean acidification significantly affects marine calcifiers like oysters, warranting the study of molecular mechanisms like DNA methylation that contribute to adaptive plasticity in response to environmental change. However, a consensus has not been reached on the extent to which methylation modules gene expression, and in turn plasticity, in marine invertebrates. In this study, we investigated the impact of pCO2 on gene expression and DNA methylation in the eastern oyster, Crassostrea virginica. After a 30-day exposure to control (572 ppm) or elevated pCO2 (2,827 ppm), whole genome bisulfite sequencing (WGBS) and RNA-Seq data were generated from adult female gonad tissue and male sperm samples. Although differentially methylated loci (DML) were identified in females (89) and males (2,916), there were no differentially expressed genes, and only one differentially expressed transcript in females. However, gene body methylation impacted other forms of gene activity in sperm, such as the maximum number of transcripts expressed per gene and changes in the predominant transcript expressed. Elevated pCO2 exposure increased gene expression variability (transcriptional noise) in males but decreased noise in females, suggesting a sex-specific role of methylation in gene expression regulation. Functional annotation of genes with changes in transcript-level expression or containing DML revealed several enriched biological processes potentially involved in elevated pCO2 response, including apoptotic pathways and signal transduction, as well as reproductive functions. Taken together, these results suggest that DNA methylation may regulate gene expression variability to maintain homeostasis in elevated pCO2 conditions and could play a key role in environmental resilience in marine invertebrates.

Alcohol consumption and high-fat diets often coincide in Western society, exerting negative synergistic effects on the liver. While many studies have demonstrated the impact of ALD and NAFLD on organ protein expression, none have offered a comprehensive view of the dysregulation at the level of the membrane proteome. In this study, we utilize peptidisc and solvent precipitation (SP4) methods to isolate and compare the membrane protein content of the liver with its unique biological functions. Using mice treated with a high-fat diet and ethanol in drinking water, we identified 1,563 liver proteins, with 46% predicted to have a transmembrane segment. Among these, 106 integral membrane proteins are dysregulated compared to the untreated sample. Gene ontology analysis reveals several dysregulated membrane processes associated with lipid metabolism, cell adhesion, xenobiotic processing, and mitochondrial membrane formation. Pathways related to cholesterol and bile acid transport are also mutually affected, suggesting an adaptive mechanism to counter the steatosis of the liver model. Our peptidisc-based membrane proteome profiling thus emerges as an effective way to gain insights into the role of the transmembrane proteome in disease development, warranting further in-depth analysis of the individual effect of the identified dysregulated membrane proteins.

Plasma extracellular vesicles (EVs) are considered excellent sources for biomarker discovery since they carry signatures of their cellular origin and disease processes. In this paper, we evaluate the potential of plasma EV proteomics analysis for identifying predictive biomarkers of developing type 1 diabetes (T1D), which results from autoimmune destruction of insulin-producing {beta} cells in the islet. We used strong anion exchange beads (Mag-Net) to capture plasma EVs from 19 donors with islet autoimmunity (diagnosed by circulating autoantibodies against islet proteins - AAB+) vs. 17 control individuals and analyzed their protein cargo by mass spectrometry. The analysis identified and quantified 5,480 proteins, a 3.2-fold increase in proteome coverage compared to our previous T1D biomarker proteomics study that used whole plasma depleted of the 14 most abundant proteins. The Mag-Net approach also detected 1,306 out of the 1,717 proteins (76%) that we previously verified as EV proteins. Statistical tests revealed 448 proteins to be differentially abundant in AAB+ vs control volunteers, including 69 previously verified EV proteins. A functional-enrichment analysis resulted in overrepresentation of 25 pathways among the differentially abundant proteins, including pathways related to autoimmune response and lipid metabolism. The capacity of this data to predict AAB+ was tested with a machine learning analysis using a random forest model, resulting in a receiver operating characteristic-area under the curve of 0.81. Overall, our study indicates that plasma EV proteomics analysis can be an exciting approach for studying biomarkers for developing T1D. Significance of the studyType 1 diabetes (T1D) is a disease characterized by the bodys inability to produce insulin and consequently, to control blood glucose levels. Despite the initial trigger being unclear, the disease development process involves an autoimmune response to the islets of Langerhans, resulting in the death of insulin-producing {beta} cells. There is no cure for the disease, and treatment relies on exogenous administration of insulin. Therefore, preventive therapies that block the autoimmune process are attractive for treating T1D. In fact, anti-CD3 antibody (Teplizumab) delays the onset of T1D by 2 years by targeting T cells. Predictive biomarkers for developing T1D are needed to aid the development and implementation of new therapies and to identify the initial trigger and mechanisms of the islet autoimmune process. In this paper, we assess the potential of plasma extracellular vesicle (EV) proteomics analysis for identifying predictive biomarkers of T1D. Our results show excellent potential of the approach, opening opportunities to perform broader studies to identify biomarkers for developing T1D.

Many of the molecular mechanisms affected by ubiquitylation are highly conserved from yeast to humans and are associated to a plethora of diseases including cancers. To elucidate the regulatory role of epigenetic factors such as the catalytic subunits of SAGA complex, KAT-Gcn5 and Ub-protease Ubp8, on ubiquitylation of non-histone proteins we have performed a comprehensive analysis of the Ub-proteome in yeast Saccharomyces cerevisiae in strains disrupted in Gcn5, Ubp8 or both respect to wild type. We found significative alteration of ubiquitylation in proteins belonging to different functional categories with a recurrence of identical proteins in absence of Gcn5 or Ubp8 indicating shared targets and their interlaced function. Among the processes involved we noteworthy identified all major enzymes engaged in energy metabolism and glycolysis such as PFK1, PFK2 and others showing increased ubiquitylation respect to WT. We showed that the higher degree of ubiquitylation found is at post-translational level and does not depend on transcription. Noteworthy, we found in vivo severe defects of growth in poor sugar medium and inability to adaptive switch from fermentative to respiratory growth in strains lacking Gcn5 and Ubp8. Our findings data provide a novel, direct link, between metabolism and epigenetic control with a novel role of DUB-Ubp8 and KAT-Gcn5 on the ubiquitylation marking all the main glycolytic enzymes required for an effective execution of the glycolytic flux. Collectively our experimental results and the proposed model can lead to future research and innovative strategies that by targeting epigenetic modulators might be able to lower sugar utilization also in human cells.\n\nAuthor SummaryMolecular mechanisms dissected in simple yeast might be translated to similar circuitries in human cells for new discoveries in human diseases including cancer. Ubiquitylation of proteins is an evolutionary conserved mechanism required for many biological processes. Different post-translational modifications (PTMs) such as ubiquitylation, acetylation, methylation etc. are reciprocally regulated for deposition or removal. Epigenetic factors writing the PTMs code are often components of multiproteic complexes such as SAGA complex that holds the K-acetyltransferase (KAT) Gcn5 and the Ubiquitin-protease (DUB) Ubp8 highly conserved in Evolution. Cells respond to environment and nutrients by changing metabolism and group of enzymes involved in specific pathways are often coregulated by the deposition of selected PTMs. This study analyses the composition and quantitation of Ub-proteins differentially modified in absence of KAT-Gcn5 and DUB-Ubp8 in yeast. Interstingly, we highlighted the role of Gcn5/Ubp8 dependent ubiquitylation in marking major glycolytic enzymes necessary for glucose utilization. Our study suggests a novel regulatory pathway and, considering that lowering glycolysis is a promising strategy to target tumor metabolism, we propose this study as an interesting perspective to lower enhanced glycolysis in tumors.

Proximity labelling that uses promiscuous biotin ligases (BirA) fused to a bait protein is a powerful tool to identify protein interaction partners in vivo under different metabolic or developmental conditions. BirA can also be used to determine protein composition and interaction partners at specific chromatin locations when it is fused with enzymatically-disabled Cas9 (dCas9) and then guided to the location of interest by sgRNAs. We adapted this method (called CasID) for fungal cells using the nitrate assimilation gene cluster of A. nidulans as a model locus and estrogen-inducible expression of the dCas9-BirA fusion to improve condition-specific labelling. For method establishment, we first verified the presence of dCas-BirA and a known transcription factor at the nitrate locus by chromatin immunoprecipitation (ChIP). Results show that both dCas-BirA and the AreA transcription factor are present at the locus of interest under the conditions used for biotinylation. We then optimized the CasID procedure for efficient labelling and background reduction using the CasID-sgRNA strain and two control strains, one lacking the sgRNA and another one lacking the whole CasID system. Here we provide proof-of-concept for the suitability of the method by showing that biotinylated proteins are enriched in the CasID strains in comparison to the controls. After background reduction, 32 proteins remained in two independent experiments exclusively enriched in the Cas-ID-sgRNA strain. Among these proteins was NmrA, an AreA-interacting regulator, and we also found several chromatin-associated proteins. Overall, our results demonstrate that Cas-ID is suitable for locus-specific labelling and identification of chromatin-associated proteins and transcription factors in A. nidulans. However, the high background of proteins that are biotinylated out of chromatin context or unspecifically attach to the affinity purification matrix needs to be addressed by implementing a set of rigorous controls. In summary, we herewith provide a detailed protocol for application of the method that proved to be useful for the identification of novel chromatin-associated proteins and their interaction partners at a specific genomic locus in divers metabolic and developmental conditions. Author summaryThis study demonstrates that locus-specific proteomics can be carried out by dCas-BirA guided proximity labelling in Aspergillus nidulans. For establishment, we targeted the well-described bidirectional promoter region between niaD, a nitrate reductase, and niiA, a nitrite reductase. At this locus we could test by chromatin immunoprecipitation (ChIP) in combination with qPCR if both, the dCas9-BirA fusion as well as a central transcription factor are at the locus under the conditions of our Cas-ID experiment. After this first control step, we considered that unspecific labelling by dCas-BirA during the time from translation to landing at the targeted chromatin locus may be one of the most relevant drawbacks of the method. Therefore, we developed a number of control strains that would allow us to clearly discriminate between background and sgRNA-dependent specific labelling at the locus. Our protein MS results validated these estimates and only considering the results of these controls enabled us to distinguish the set of locus-specific proteins from a very high general background. Finally, enrichment of biotinylated proteins through affinity purification with streptavidin resin and subsequent LC-MS/MS analysis showed that more than 800 proteins were detected in each sample, emphasizing the high background of the purification method. After background reduction of the control samples, we were able to identify 32 proteins which were exclusively detected in the test strain in two independent measurements, including several chromatin-associated proteins and NmrA, a negative regulator of the nitrate locus transcription factor AreA.

Microbial metabolites affect the neuron system and muscle cell functions. Amyotrophic Lateral Sclerosis (ALS) is a multifactorial neuromuscular disease. Our previous study has demonstrated elevated intestinal inflammation and dysfunctional microbiome in ALS patients and an ALS mouse model (human-SOD1G93A transgenic mice). However, the metabolites in ALS progression are unknown. Using an unbiased global metabolomic measurement and targeted measurement, we investigated the longitudinal changes of fecal metabolites in the SOD1G93A mice over the course of 13 weeks. We compared the changes of metabolites and inflammatory response in age-matched WT and SOD1G93A mice treated with bacterial product butyrate. We found changes in carbohydrate levels, amino acid metabolism, and formation of gamma-glutamyl amino acids. Shifts in several microbially-contributed catabolites of aromatic amino acids agree with butyrate-induced changes in composition of gut microbiome. Declines in gamma-glutamyl amino acids in feces may stem from differential expression of GGT in response to butyrate administration. Due to signaling nature of amino acid-derived metabolites, these changes indicate changes in inflammation (e.g. histamine) and contribute to differences in systemic levels of neurotransmitters (e.g. GABA, glutamate). Butyrate treatment was able to restore some of the healthy metabolites in ALS mice. Moreover, microglia in the spinal cord were measured by the IBA1 staining. Butyrate treatment significantly suppressed the IBA1 level in the SOD1G93A mice. The serum IL-17 and LPS were significantly reduced in the butyrate treated SOD1G93A mice. We have demonstrated an inter-organ communications link among metabolites, inflammation, and ALS progression, suggesting the potential to use metabolites as ALS hallmarks and for treatment. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/476456v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@16d3e4dorg.highwire.dtl.DTLVardef@1155c05org.highwire.dtl.DTLVardef@14c6155org.highwire.dtl.DTLVardef@18a30d6_HPS_FORMAT_FIGEXP M_FIG We compared the changes of metabolites and inflammatory response in age-matched WT and SOD1G93A mice treated with bacterial product butyrate. Butyrate treatment was able to restore some of the healthy metabolites in ALS mice. Due to signaling nature of amino acid-derived metabolites, these changes indicate changes in inflammation and contribute to differences in systemic levels of neurotransmitters (e.g. GABA, glutamate). Moreover, butyrate treatment significantly suppressed the microglia IBA1 level and aggregated SOD1G93A in the SOD1G93A mice. The inflammatory cytokine, e.g serum IL-17, was significantly reduced in the butyrate treated SOD1G93A mice. We have demonstrated an inter-organ communications link among metabolites, inflammation, and ALS progression, suggesting the potential to use metabolites as ALS hallmarks and for treatment. C_FIG

Hydrogen peroxide (H2O2) functions as a secondary messenger in cellular redox signaling, acting mainly via oxidation of protein thiols. Its spatially and temporally regulated activity within cells is essential for maintaining proper redox balance, and disruptions in these patterns can lead to oxidative stress and various related pathologies. Redox proteomics, which examines the impact of H2O2 at the proteome level, typically focuses only on thiol oxidation, overlooking broader proteomic alterations and the significance of subcellular localization in these redox processes. In this study, we address these open questions by combining chemogenetics with Thermal Proteome Profiling (TPP) to map global proteome response to compartmentalized H2O2 production. We identified hundreds of proteins with altered thermostability and/or abundance upon localized H2O2 generation in the cytosol, nucleus, and the ER lumen, highlighting their roles in cellular responses to localized H2O2. We identified proteins such as MAP2K1, PARK7, TRAP1, and UBA2 to be highly sensitive to localized H2O2 production. Furthermore, we validated their altered thermostability and found that these changes are controlled via dysregulated protein-protein interactions. This study provides a valuable resource for researchers exploring redox-mediated signal transduction and offers novel insights that could be harnessed in treating oxidative stress-induced pathologies.

The prefoldin complex (PFDc) participates in cellular proteostasis in eukaryotes by acting as cochaperone of the chaperonin CTT. This role is mainly exerted in the cytoplasm where it contributes to the correct folding of client proteins, thus preventing them to form aggregations and cellular damage. Several reports indicate, however, that they also play a role in transcriptional regulation in the nucleus in several model species. In this work, we have investigated how extended is the role of PFDs in nuclear processes by inspecting their interactome and their coexpression networks in yeast, fly, and humans. The analysis indicates that they may perform extensive, conserved functions in nuclear processes. The construction of the predicted interactome for Arabidopsis PFDs, based on the ortholog interactions, has allowed us to identify many putative PFD interactors linking them to unanticipated processes, such as chromatin remodeling. Based on this analysis, we have investigated the role of PFDs in H2A.Z deposition through their interaction with the chromatin remodeling complex SWR1c. Our results show that PFDs have a positive effect on SWR1c, which is reflected in defects in H2A.Z deposition in hundreds of genes in seedlings defective in PFD3 and PFD5 activities.

Cell type identity is determined by gene regulatory networks (GRNs), comprising the expression of specific transcription factors (TFs) regulating target genes (TGs) via binding to open chromatin regions (OCRs). The regulatory logic of differentiation includes factors specific to one or multiple cell types, functioning in a combinatorial fashion. Classic approaches of GRN discovery used perturbational data to elucidate TF-TG links, but are laborious and not scalable across the tree of life. Single cell transcriptomics has emerged as a revolutionary approach to study gene expression with cell type resolution, but incorporating perturbational data is challenging. Planarians, with their pluripotent neoblast stem cells continuously giving rise to all cell types, offer an ideal model to attempt this integration. Despite extensive single cell transcriptomic studies, the transcriptional and chromatin regulation at the cell type level remains unexplored. Here, we investigate the regulatory logic of planarian stem cell differentiation by obtaining an organism-level integration of single cell transcriptomics and single cell accessibility data. We identify specific open chromatin profiles for major differentiated cell types and analyse their transcriptomic landscape, revealing distinct gene modules expressed in individual types and combinations of them. Integrated analysis unveils gene networks reflecting known TF interactions in each type and identifies TFs potentially driving differentiation across multiple cell types. To validate our predictions, we combined TF knockdown RNAi experiments with single cell transcriptomics. We focus on hnf4, a TF known to be expressed in gut phagocytes, and confirm its influence on other types, including parenchymal cells. Our results demonstrate high overlap between predicted targets and experimentally-validated differentially-regulated genes. Overall, our study integrates TFs, TGs and OCRs to reveal the regulatory logic of planarian stem cell differentiation, showcasing that the combination of single cell methods and perturbational studies will be key for characterising GRNs widely.

Polycomb Repressive Complex 2 (PRC2), an important histone modifier and epigenetic repressor, has been known to interact with RNA for almost two decades. In our previous publication (Long, Hwang et al. 2020), we presented data supporting the functional importance of RNA interaction in maintaining PRC2 occupancy on chromatin, using comprehensive approaches including an RNA-binding mutant of PRC2 and an rChIP-seq assay. Recently, concerns have been expressed regarding whether the RNA-binding mutant has impaired histone methyltransferase activity and whether the rChIP-seq assay can potentially generate artifacts. Here we provide new data that support a number of our original findings. First, we found the RNA-binding mutant to be fully capable of maintaining H3K27me3 levels in human induced pluripotent stem cells. The mutant had reduced methyltransferase activity in vitro, but only on some substrates at early time points. Second, we found that our rChIP-seq method gave consistent data across antibodies and cell lines. Third, we further optimized rChIP-seq by using lower concentrations of RNase A and incorporating a catalytically inactive mutant RNase A as a control, as well as using an alternative RNase (RNase T1). The EZH2 rChIP-seq results using the optimized protocols supported our original finding that RNA interaction contributes to the chromatin occupancy of PRC2.

Amyloids are proteinaceous fibrillar structures and are known for their pathogenic and functional roles across the kingdoms. Besides proteinaceous deposits, amyloid-like structures are present in small metabolite assemblies and fibrillar hydrogels. Recent cryoelectron microscopy studies have shed light on the heterogeneous nature of the amyloid structures and their association with carbohydrate or lipid molecules, suggesting that amyloids are not exclusively proteinaceous. The association of amyloids with carbohydrates is further supported because the gold-standard dye of amyloid detection, Congo red, also binds to carbohydrates, probably due to similar stacking interactions. We name the association between amyloids, carbohydrates and other biomolecules as amyloid-network and propose that plants might contain such structures. Specifically, we hypothesize that cereal seeds containing glutamine-repeat-rich granules of storage proteins may have amyloid-like structures. This is because, polyQ repeats are associated with protein aggregation and amyloid formation in humans and are linked to multiple neurodegenerative conditions. Also seed storage proteins and seed cell wall proteins possess carbohydrate affinity. Thus, plant seeds might contain an intercalated network of proteins and carbohydrates, lending strength, stability and dynamics to these structures. In this paper, we show that, plant seeds have a mesh-like network that shows apple-green birefringence on staining with Congo red, a characteristic of amyloids. This congophilic network is more prominent in protein-rich seed sections of wheat and lentils, as compared to starch-rich compartments of potato. The findings suggest an amyloid network in the seeds and might be extended to other plant tissues. Further investigation with mass spectrometry and other techniques would detail the exact compositional analysis of these networks.

The COVID-19 disease has been a global threat caused by the new coronavirus species, SARS-CoV-2, since early 2020 with an urgent need for therapeutic interventions. In order to provide insight into human proteins targeted by SARS-CoV-2, here we study a directed human protein-protein interaction network (dhPPIN) based on our previous work on network controllability of virus targets. We previously showed that human proteins targeted by viruses tend to be those whose removal in a dhPPIN requires more control of the network dynamics, which were classified as indispensable nodes. In this study we introduce a more comprehensive rank-based enrichment analysis of our previous dhPPIN for SARS-CoV-2 infection and show that SARS-CoV-2 also tends to target indispensable nodes in the dhPPIN using multiple proteomics datasets, supporting validity and generality of controllability analysis of viral infection in humans. Also, we find differential controllability among SARS-CoV-2, SARS-CoV-1, and MERS-CoV from a comparative proteomics study. Moreover, we show functional significance of indispensable nodes by analyzing heterogeneous datasets from a genome-wide CRISPR screening study, a time-course phosphoproteomics study, and a genome-wide association study. Specifically, we identify SARS-CoV-2 ORF3A as most frequently interacting with indispensable proteins in the dhPPIN, which are enriched in TGF-beta signaling and tend to be sources nodes and interact with each other. Finally, we built an integrated network model of ORF3A-interacting indispensable proteins with multiple functional supports to provide hypotheses for experimental validation as well as therapeutic opportunities. Therefore, a sub-network of indispensable proteins targeted by SARS-CoV-2 could serve as a prioritized network of drug targets and a basis for further functional and mechanistic studies from a network controllability perspective.

Urine based biomarker discovery employing proteomics platform has been successfully attempted for multiple diseases. Urine is an excellent source of biomarker discovery but its potential is not fully tapped in tuberculosis (TB) diagnostics. In the present study, proteomic profiling of urine samples from thirty five subjects (Mean age=41 years (15-76), M/F=28/7) belonging to active TB, latent TB, lung cancer, chronic obstructive pulmonary disorders (COPD) and healthy subjects were carried out employing a robust multiplex technique. We identified 131 proteins out of which 16 molecules showed at least two-fold change in TB. The study identified a signature of three putative markers, leucine-rich alpha-2-glycoprotein (up-regulated), roundabout homolog 4 and isoform 2 of prostatic acid phosphatase (down-regulated) that could differentiate active TB from other pulmonary diseases. Besides, we investigated whether a network based approach can be efficiently used to expand dynamic coverage, gain a comprehensive view of underlying perturbed functions during the infection and to discover potential biomarkers. While comparing the functionally associated sub-networks of active TB with healthy urine proteome, we identified 54 proteins from the discriminative TB sub-network, some of which are known to be involved in the infection process. Few examples in this study like serpin peptidase inhibitor and catenin that has not been identified in the experiment but detected in the difference network demonstrate that proteomic profiling when integrated with network biology method could be a holistic approach to expand the dynamic range and identify potential candidate biomarkers and also provide a broad overview of perturbed functions during the infection.

Mesenchymal stem cells (MSCs) are widely used as therapeutics targets for numerous autoimmune diseases. However, MSC therapies have had limited success so far in clinical trials, mainly being heterogenous population it is difficult to determine MSCs efficiencies. It is critical to understand internal signaling of individual MSCs population that directly affect the cell phenotype. Lipid signaling is closely associated with cell shape so, a holistic approach to understand how changes in lipid metabolites trickles all the way to single cell phenotype could reveal deeper understanding of MSCs functional regulation. So, we aim to evaluate lipid metabolic profiles of single cell MSCs with known variability in immune regulation and explore the phenotypic changes that occur because of differences in lipid signaling. We use longitudinal label free phase imaging strategies to obtain cell phenotypic features which are directly correlated with single cell lipid metabolome obtained using advanced MALDI-MSI technique. Correlation maps indicate associations between lipid signaling and phenotypic changes in MSCs. Moreover, a novel machine learning clustering approach detects the heterogeneity in the MSCs subpopulation then methodically see how each heterogenous population is being impacted by the changes in lipid profiles which could be linked to the functional behaviors of the cell.