Molecular Omics

GBA1 is a risk gene for multiple neurodegenerative diseases, including Lewy Body Dementia and Parkinsons disease, and biallelic pathogenic variants in the gene result in the lysosomal storage disorder Gaucher disease. GBA1 encodes the enzyme glucocerebrosidase (GCase), and alterations in the gene result in reduced enzymatic activity, which affects lysosome function downstream. Induced pluripotent stem cells (iPSCs) are a useful tool for testing the functional consequences of gene variants in an isogenic setting. Additionally, they can be used to perform multiomic studies to explore biological effects independent of disease mechanisms. Using CRISPR-edited isogenic KOLF2.1J iPSC lines containing pathogenic GBA1 variants D409H (p.D448H), D409V (p.D448V) and GBA1 knockout line generated by the iPSC Neurodegenerative Disease Initiative (iNDI), we examined potential molecular mechanisms and downstream consequences of GCase reduction. In this study, we confirm that this isogenic series behaves as expected for loss of function variants, despite the known difficulties with GBA1 editing. We identified that there are limited overlapping results across cell types suggesting potential different downstream effects caused by GBA1 variants. Additionally, we note that RNA-based quantitation may not be the best method to characterize GCase mechanisms, but protein and metabolomic analyses may be used to evaluate differences across genotypes.

AO_SCPLOWBSTRACTC_SCPLOWThe severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is a highly contagious virus that causes a severe respiratory disease known as Corona virus disease 2019 (COVID19). Indeed, COVID19 increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The pathophysiological processes underlying COVID19-induced thrombosis are complex, and remain poorly understood. To this end, platelets play important roles in regulating our cardiovascular system, including via contributions to coagulation and inflammation. There is an ample of evidence that circulating platelets are activated in COVID19 patients, which is a primary driver of the thrombotic outcome observed in these patients. However, the comprehensive molecular basis of platelet activation in COVID19 disease remains elusive, which warrants more investigation. Hence, we employed gene co-expression network analysis combined with pathways enrichment analysis to further investigate the aforementioned issues. Our study revealed three important gene clusters/modules that were closely related to COVID19. Furthermore, enrichment analysis showed that these three modules were mostly related to platelet metabolism, protein translation, mitochondrial activity, and oxidative phosphorylation, as well as regulation of megakaryocyte differentiation, and apoptosis, suggesting a hyperactivation status of platelets in COVID19. We identified the three hub genes from each of three key modules according to their intramodular connectivity value ranking, namely: COPE, CDC37, CAPNS1, AURKAIP1, LAMTOR2, GABARAP MT-ND1, MT-ND5, and MTRNR2L12. Collectively, our results offer a new and interesting insight into platelet involvement in COVID19 disease at the molecular level, which might aid in defining new targets for treatment of COVID19-induced thrombosis. key pointsO_LICo-expression analysis of platelet RNAseq from COVID19 patients show distinct clusters of genes (modules) that are highly correlated to COVID19 disease. C_LIO_LIIdentifying these modules might help in understanding the mechanism of thrombosis in COVID19 patients C_LI

Metabolism is intricately linked with cell fate changes. Much of this understanding comes from detailed metabolomics studies averaged across a population of cells which may be composed of multiple cell types. Currently, there are no quantitative techniques sensitive enough to assess metabolomics broadly at the single cell level. Here we present scMetNet, a technique that interrogates metabolic rewiring at the single cell resolution and we apply it to murine embryonic development. Our method first confirms the key metabolic pathways, categorized into bioenergetic, epigenetic and biosynthetic, that change as embryonic neural stem cells differentiate and age. It then goes beyond to identify specific sub-networks, such as the cholesterol and mevalonate biosynthesis pathway, that drive the global metabolic changes during neural cortical development. Having such contextual information about metabolic rewiring provides putative mechanisms driving stem cell differentiation and identifies potential targets for regulating neural stem cell and neuronal biology.

Oligodendrocyte maturation and myelination are critical processes in human neurodevelopment, and their dysregulation is linked to numerous neurological disorders. While model organisms have provided insight into these processes, human-specific regulatory mechanisms remain poorly understood. This study investigated human THAP9, a protein homologous to the Drosophila P-element transposase, whose function in oligodendrocytes remains unknown. An analysis of publicly available RNA-sequencing data and H3K27ac ChIP-sequencing data from oligodendrocyte progenitor cells (OPCs) and mature oligodendrocytes (MOs) revealed significant upregulation of THAP9 during oligodendrocyte maturation. Co-expression analysis demonstrated a strong correlation with established markers of oligodendrocyte development, including myelin-associated genes (MOG, MBP) and key transcriptional regulators (PDGFRA, SOX5, SOX6, SOX11). THAP9 lacks homologues in mice, highlighting potential human-specific mechanisms in oligodendrocyte development and emphasising the importance of studying species-specific factors in neurodevelopment. Our findings suggest that THAP9 is a novel human-specific regulator of oligodendrocyte maturation and opens new avenues for studying myelination disorders.

In order to implement quality control measures and create fine flavor products, an important objective in cocoa processing industry is to realize standards for characterization of cocoa raw materials, intermediate and finished products with respect to their processing stages and countries of origin. Towards this end, various works have studied separability or distinguishability of cocoa samples belonging to various processing stages in a typical cocoa processing pipeline or to different origins. Limited amount of success has been possible in this direction in that unfermented and fermented cocoa samples have been shown to group into separate clusters in PCA. However, a clear clustering with respect to the country of origin has remained elusive. In this work we suggest an alternative approach to this problem through the framework of correlation networks. For 140 cocoa samples belonging to eight countries and three progressive stages in a typical cocoa processing pipeline we compute pairwise Spearman and Pearson correlation coefficients based on the LC-MS profiles and derive correlation networks by retaining only correlations higher than a threshold. Progressively increasing this threshold reveals, first, processing stage (or sample type) modules (or network clusters) at low and intermediate values of correlation threshold and then country specific modules at high correlation thresholds. We present both qualitative and quantitative evidence through network visualization and node connectivity statistics. Besides demonstrating separability of the two data properties via this network-based method, our work suggests a new approach for studying classification of cocoa samples with nested attributes of processing stage sample types and country of origin along with possibility of including additional factors, e.g., hybrid variety, etc. in the analysis.

One of the most important properties of human embryonic stem cells (hESCs) is related to their pluripotent states. In our recent study, we identified a previously unrecognized pluripotent state induced by RSeT medium. This state makes primed hESCs resistant to conversion to naive pluripotent state. In this study, we have further characterized the metabolic features in these RSeT hESCs, including metabolic gene expression, metabolomic analysis, and various functional assays. The commonly reported metabolic modes include glycolysis or both glycolysis and oxidative phosphorylation (i.e., metabolic bivalency) in pluripotent stem cells. However, besides the presence of metabolic bivalency, RSeT hESCs exhibited a unique metabolome with additional fatty acid oxidation and imbalanced nucleotide metabolism. This metabolic quadrivalency is linked to hESC growth independent of oxygen tension and restricted capacity for naive reprogramming in these cells. Thus, this study provides new insights into pluripotent state transitions and metabolic stress-associated hPSC growth in vitro.

Myalgic Encephalomyelitis, or Chronic Fatigue Syndrome (ME/CFS), is characterised by severe fatigue and associated with immune dysfunction. Previous studies of DNA methylation have found evidence of changes in immune cells for ME/CFS. However these studies have been limited by their small sample size. Here, we aggregate three comparable datasets to achieve a larger sample size and detect small changes to DNA methylation. We find 10,824 differentially methylated genes, with a small average change. Next, from the currently known interactions of relevant proteins, we build a Protein-Protein interaction network and,localising the network cartography analysis, we identify 184 hub genes. We find that different hub types play different, and meaningful, biological roles. Finally, we perform Gene ontology enrichment analysis, and we find that these hubs are involved in immune system processes, including response to TGF-{beta} and LPS, as well as mitochondrial functioning, supporting previous theories about ME/CFS. We also show that dopaminergic signalling may potentially contribute to immune pathology in ME/CFS, suggesting a possible interplay with Long Covid. Our results demonstrate the potentiality of network analysis in shedding light on the epigenetic contribution to the immune dysregulation of ME/CFS.

About 100 genes have been associated with significantly increased risks of autism spectrum disorders (ASD) with an estimate of [~]1000 genes that may be involved. The new challenge now is to investigate the molecular and cellular functions of these genes during neural and brain development, and then even more challenging, to link the altered molecular and cellular phenotypes to the ASD clinical manifestations. In this study, we use single cell RNA-seq analysis to study one of the top risk gene, CHD8, in cerebral organoids, which models early neural development. We identify 21 cell clusters in the organoid samples, representing non-neuronal cells, neural progenitors, and early differentiating neurons at the start of neural cell fate commitment. Comparisons of the cells with one copy of the CHD8 knockout and their isogenic controls uncover thousands of differentially expressed genes, which are enriched with function related to neural and brain development, with genes and pathways previously implicated in ASD, but surprisingly not for Schizophrenia and intellectual disability risk genes. The comparisons also find cell composition changes, indicating potential altered neural differential trajectories upon CHD8 reduction. Moreover, we find that cell-cell communications are affected in the CHD8 knockout organoids, including the interactions between neural and glial cells. Taken together, our results provide new data for understanding CHD8 functions in the early stages of neural lineage development and interaction.

The integration of genome data with electronic health records, driven by large biobank studies, has advanced human genetics by allowing systematic exploration of genotype-phenotype links. Regular donation enables large, longitudinal sample cohorts. Because blood donors are generally healthy, disease treatments or progression do not disturb interpretations in functional studies. We describe here a pipeline on how to collect blood donors high quality plasma, serum, and living cell samples for multi-omics studies. Peripheral blood mononuclear cells (PBMC) were frozen and, after thawing, contained standard levels of immune cell subpopulations, responded to immune activation, and were of good quality starting material for multi-omics and cell imaging studies. We demonstrate that most genetic variants of interest to the major genomics study in Finland, FinnGen, could be found by random collection of samples during the standard blood donation without recall. Probing simple associations in the multi-omics data confirmed expected associations with e.g. age and sex, demonstrating good sample quality. As an example of interesting findings, we observed a significant association between frequent blood donation and lower levels of per- and polyfluoroalkyl substances (PFAS). The study demonstrates that regular blood donors are a suitable target population for high-quality, cost-effective sample collections.

Hyperornithinaemia with gyrate atrophy of choroid and retina (HOGA) is a recessive metabolic disease caused by dysfunction of the ornithine aminotransferase (OAT) gene, leading to ornithine accumulation and a complex metabolic imbalance. This causes retinal degeneration that ultimately evolve to blindness. However, the mechanisms of this degeneration remain unknown. Here, we have conducted untargeted metabolomic analysis in patient-derived induced pluripotent stem cells and their isogenic counterparts. Mutant cells show altered levels of ornithine-related metabolites, including low creatine, proline and glutamate, and elevated arginine and citrulline. The untargeted metabolomics approach revealed changes in the urea cycle and polyamine synthesis pathways with a significant intracellular accumulation of gamma-aminobutyric acid (GABA). Hence, we propose GABA as a key player in the disease pathogenicity, potentially affecting neuronal function in the eye.

Cannabis sativa L. (marijuana, hemp, cannabis) is an angiosperm species currently evolving sex chromosomes. Genetic mechanisms, primarily an XY chromosome system, dictate cannabis sex expression in dioecious populations. However, sexual expression is also governed by the interplay of hormone regulatory gene networks, influenced by both genetic and environmental factors. Within the species, some populations exhibit dioecy, monoecy, or a gradient of both. Dioecious individuals produce exclusively male or female flowers, while monoecious plants bear both male and female flowers. Remarkably, through interruption of phytohormone signal transduction via abiotic stressors, genetically male or female cannabis are able to produce flowers of the opposite sex. Previous transcriptomic analysis have identified genes associated with masculinization through the application of phytohormone signal disruption using silver thiosulfate treatment. We analyzed transcriptomic data from cannabis treated with colloidal silver to similarly induce masculinization. Using Nota (Network Ontology Transcript Annotation), a multilayer network analysis (random walk with restart) tool, we identified candidate genes involved in sex-determination. Nota and a companion program Jack facilitate multi-layer network analyses, enabling discovery and annotation of gene-trait associations. Our findings highlight Notas robust application to enrich the genetic architecture of complex traits, particularly in non-model systems like cannabis, and complex traits such as sex determination. Our analyses identified genes associated with cell wall morphogenesis and embryogenic tissue homeostasis, indicating that silver ion treatment perturbs phytohormone signal transduction through metal ion imbalance. In this reproductive strategy, cannabis is able to make use of its widely investigated sex-determining genetic architecture to navigate transient changes in co-expression and cross-cellular signaling driving embryogenic cell wall re-patterning.

The role of oligodendrocytes in neurodegenerative diseases remains incompletely understood and largely unexplored at the single cell level. We profiled 87,086 single nuclei from human brain putamen region for healthy control, Parkinsons Disease (PD), and Multiple System Atrophy (MSA). Oligodendrocyte lineage cells were the dominant cell-type in the putamen with oligodendrocyte subpopulations clustered by transcriptomic variation found to exhibit diverse functional enrichment patterns, and this oligodendrocyte heterogeneity was altered in a disease-specific way. Among profiled oligodendrocyte subpopulations, differences in expression of SNCA, HAPLN2, MAPT, APP, and OPALIN were observed for PD and MSA compared with healthy controls. Intriguingly, greater activation of unfolded protein response pathway gene expression was observed in PD nuclei versus MSA. Using network analysis, we then identified specific PD- and MSA-correlated gene co-expression modules enriched with disease relevant pathways; the PD-correlated module was significantly enriched for Parkinsons Disease GWAS loci (p = 0.01046). Our analysis provides a broader understanding of oligodendrocyte heterogeneity and reveals distinctive oligodendrocyte pathological alterations associated with PD and MSA which may suggest potential novel therapeutic targets and new strategies for disease modification.

Neuronal differentiation is a complex process that entails extensive morphological, transcriptional, metabolic, and functional changes that dictate neuronal lineage commitment. Much less understood is the role that epigenetic and epi-transcriptional reprogramming plays in the process of neuronal differentiation and maturation. To depict the whole landscape of transcriptomics and epigenetic changes during neuronal differentiation and maturation, we differentiated SH-SY5Y cells and performed RNA sequencing on differentiated and undifferentiated cells. 728 differentially expressed genes (DEGs) enriched in synaptic signaling and cell morphogenesis pathways were observed. Moreover, transcriptome-wide mRNA stability profiling revealed that genes with altered stability were exceptionally enriched for redox homeostasis pathways. Mature neurons are known to be highly sensitive to oxidative stress, which is crucial in the pathophysiology of neurodegenerative disease. Our results suggest that this heightened sensitivity is regulated at the mRNA stability level (i.e., epigenetic) rather than at the transcriptional level. Alternative splicing analysis revealed the exon skipping and alternative mRNA isoforms enriched for morphogenesis related pathway. Alternatively, alternative 5 and 3 prime splicing site, intron retention and mutually exclusive exon events exclusively clustered in the translation and translation initiation pathways, suggesting the potential effect of alternative splicing on translation following neuronal maturation. Splice motif analysis revealed enriched motifs for RBPs that regulate various splice types and can be further correlated to distinct phenotypical changes during neuronal differentiation and maturation. Here we present an extensive exploration of the transcriptional and epigenetic changes and their potential association with the process of neuronal differentiation, providing a new insight into understanding the molecular mechanism of neuronal function and behavior.

Balancing SAM allocations for methylation reactions, and maintaining the SAM/SAH ratio is crucial for cellular homeostasis. How cells balance the allocation of methyl pools between different sinks, remains under studied. In this study using S. cerevisiae, we identify a role of the amino acid response regulator Gcn4 (Atf4) in balancing the methyl allocations between phospholipids and histones when methionine is abundant. Here, when SAM/SAH ratio increases during methionine supplementation, Gcn4-dependent outputs critically regulate the appropriate allocation of methyl pools to phospholipids and histones. Gcn4 regulates phospholipid methylation by controlling Ino2 levels, which is a primary transcriptional regulator of phospholipid biogenesis. In the absence of Gcn4, Ino2 levels decrease, leading to the downregulation of the PE methyltransferases Cho2 and Opi3. This downregulation of these methyltransferases reduces SAM consumption for phospholipid biosynthesis, and in turn elevates the SAM/SAH ratio in the cell. The elevated SAM pools are subsequently re-allocated towards histone hyper-methylation. Our study reveals the novel role of Gcn4 as a regulator of phospholipid biosynthesis during methionine sufficiency, highlighting its role in appropriate methyl allocations in cells. This Gcn4-dependent check on methylation is therefore necessary to enable cell proliferation when SAM pools are abundant.

The Golgi is a dynamic organelle with a unique morphology that has implications on its function. How the structural integrity of the Golgi is maintained despite its dynamic nature has been a long-standing question. Several siRNA-based screens have addressed this question and have identified a number of key players required for Golgi integrity. Interestingly, they also reported heterogeneity of phenotypic responses with regards to Golgi morphology. Although never systematically investigated, this variability has generally been attributed to poor transfection efficiency or cell cycle specific responses. Here we show that this heterogeneity is the result of differential response to the siRNA knockdown in different Golgi phenotypes, independent of transfection efficiency or cell cycle phases. To characterize the observed Golgi phenotype-specific responses at the molecular level we have developed an automated assay which enables microscopy-based phenotype classification followed by phenotype-specific single-cell transcriptome analysis. Application of this novel approach to the siRNA mediated knockdown of USO1, a key trafficking protein at the ER to Golgi boundary, surprisingly suggests a key involvement of the late endosomal/endocytic pathways in the regulation of Golgi organization. Our pipeline is the first of its kind developed to study Golgi organization, but can be applied to any biological problem that stands to gain from correlating morphology with single-cell readouts. Moreover, its automated and modular nature allows for uncomplicated scaling up, both in throughput and in complexity, helping the user achieve a systems level understanding of cellular processes.

Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) is the leading cause of childhood end-stage renal disease and a significant cause of chronic kidney disease in adults. Genetic and environmental factors are known to influence CAKUT development, but the currently known disease mechanism remains incomplete. Our goal is to identify affected pathways and networks in CAKUT, and thereby aid in getting a better understanding of its pathophysiology. Multi-omics experiments, including amniotic fluid miRNome, peptidome, and proteome analyses, can shed light on foetal kidney development in non-severe CAKUT patients compared to severe CAKUT cases. We performed FAIRification of these omics data sets to facilitate their integration with external data resources. Furthermore, we analysed and integrated the omics data sets using three different bioinformatics strategies. The three bioinformatics analyses provided complementary features, but all pointed towards an important role for collagen in CAKUT development. We published the three analysis strategies as containerized workflows. These workflows can be applied to other FAIR data sets and help gaining knowledge on other rare diseases.

Emerging evidence indicates an intricate relationship between the SARS-CoV-2 infection and Multi-Organ Dysfunctions (MODs). Here, we have investigated the role of the Secretome of the SARS-CoV-2 infected pancreas and mechanistically linked it with the multi-organ dysfunction using the scRNA-seq analysis. We found that acinar-specific PRSS2, REG3A, REG1A, SPINK1, and ductal-specific SPP1, MMP7 genes are upregulated in alpha, beta, delta, and mesenchyme cells. Using extensive documented experimental evidence, we validated the association of upregulated pancreatic Secretome with coagulation cascade, complement activation, renin angiotensinogen system dysregulation, endothelial cell injury and thrombosis, immune system dysregulation, and fibrosis. Our finding suggests the influence of upregulated Secretome on multi-organ systems such as Nervous, Cardiovascular, Immune, Digestive, and Urogenital systems. In addition, we report that the secretory proteins IL1B, AGT, ALB, SPP1, CRP, SERPINA1, C3, TFRC, TNFSF10, and MIF are associated with diverse diseases. Thus, suggest the role of the pancreatic Secretome in SARS-CoV-2 associated MODs.

BackgroundParkinsons disease (PD) is characterized by diverse clinical presentations and etiological complexities, with rapid eye movement (REM) sleep behavior disorder (RBD) serving as a prodromal marker. While extensive unbiased metabolic profiling of plasma samples from PD subjects has been conducted to identify novel PD metabolic biomarkers, comprehensive metabolic profiling of PD subtypes based on RBD status remains limited. MethodsWe conducted a comprehensive metabolic profiling of PD subtypes at disease onset, considering the presence or absence of RBD, utilizing an untargeted metabolomics approach. Plasma samples were collected from subjects with PD with and without RBD at the initial stages of disease, idiopathic RBD, and healthy controls to elucidate similarities and differences among PD subtypes. Based on ordination analysis and metabolome-wide association study (Wilcoxon rank-sum tests and generalized fold changes), we identified specific groups of metabolites enriched in the PD_Only group and RBD groups (iRBD & PD_RBD+), with few metabolites shared between groups. Furthermore, pathway enrichment analysis (hypergeometric tests) identified specific groups enriched with metabolites from specific origins and associated biospecimens, as well as disease-associated metabolites. Finally, we evaluated the biomarker potential of the identified disease metabolites by ROC curves and proposed logistic regression models of key biomarkers and clinical parameters for predicting disease status. ResultsMetabolomic analysis revealed distinct metabolic profiles between PD subtypes with and without RBD. Our analysis confirmed previously reported PD metabolic markers, such as a reduction in caffeine and urate, as well as an increase in cortisol, secondary bile acids, and p-cresol sulfate. However, our stratified analyses based on the presence of RBD discriminated RBD-associated metabolites from those associated with PD_Only (without RBD). PD patients with RBD exhibited enrichment of gut microbial-origin metabolites, including secondary bile acids and p-cresol sulfate, compared to PD patients without RBD. Conversely, metabolites associated with neuro-psychiatric diseases were enriched in PD patients without RBD. ConclusionsOur study elucidates the heterogeneous nature of PD subtypes, particularly differentiated with the presence of RBD. The metabolic features of PD with RBD subtype supports the "body-first" concept of PD pathogenesis originating from the gut.

BackgroundGlycogen Storage Disease (GSD) Types Ia and Ib are rare metabolic diseases caused by gene variants in G6PC1 and SLC37A4, respectively. Although life-threatening fasting hypoglycemia can be controlled by a strict diet, patients often suffer from multiple metabolic abnormalities and severe long-term complications. However, the underlying mechanisms remain incompletely understood, and the lack of effective monitoring biomarkers makes it a challenge to treat patients. Therefore, the aims of this study are to investigate the pathological mechanisms of the disease and disease complications in GSD I and identify potential protein biomarkers. MethodsIn this study, we employed comprehensive untargeted proteomics on stored samples: 26 serum or plasma samples from 18 GSD Ia and 8 GSD Ib patients with 21 matched control sera, complemented by 4 liver samples from 2 GSD Ia patients who received liver transplantation (from the one patient with hepatocellular carcinoma we obtained tissue from both the carcinoma tissue and the adjacent non-carcinoma tissue), and 1 from a GSD Ib patient, compared to 10 donor liver samples. ResultsWe identified a total of 415 proteins in our analyses. Pathway analysis of the differentially regulated proteins revealed distinct changes in serum/plasma of GSD Ia and Ib. The coagulation pathway was the most significantly changed biological process in the GSD Ia patients. Immune response-associated proteins, especially a large number of immunoglobulins, were increased in GSD Ib specifically. Proteins related to liver injury, cholesterol, and amyloidosis were altered in two subtypes, though more pronounced in GSD Ia. Potential biomarkers with significant alterations both in the circulation as well as in the liver tissue were identified specifically for monitoring GSD I subtypes and prognosing liver deterioration, namely GSD Ia (COL163 and PROC), GSD Ib (F11 and CD163), and hepatocellular carcinoma (HCC) in GSD Ia patients (ALDOB and CFHR5). ConclusionsThese findings provide new insights into the differences between the two GSD I subtypes and the pathogenesis of GSD I-related complications, as well as highlighting the potential of protein circulating biomarkers for monitoring complication progression in GSD I and assessing HCC risk in GSD Ia patients. Trial registrationNot applicable. A concise 1 sentence take-home message (synopsis) of the articleThis comprehensive in-depth proteomics study on blood and liver GSD Ia and Ib patient samples provided novel insights into understanding of the disease subtypes as well as the the pathogenesis of GSD I-related complications, such as HCC risk in GSD Ia patients and identified potential biomarkers for the disease subtypes and complications.

During manufacturing batches, Chinese hamster ovary (CHO) cells encounter critical levels of environmental stressors such as ammonia, lactate, and osmolality accumulation that can significantly reduce cell health and productivity. It is therefore crucial that stress adaptation and resistance be factored into cell line development (CLD). In this study, we employee population-based transcriptomic and differential gene expression analysis on stress-induced CHO cells to identify biomarkers displaying both heritable and stress-responsive properties. Using this workflow, 199 genes displayed transcriptional variability characteristic of a bistable system that formed four network communities of co-fluctuating genes. These communities were enriched in genes related to the regulation of apoptotic processes and gene expression/metabolic pathways. Seven genes were identified as promising biomarkers for engineering a stress-resistant phenotype. Genetic engineering methods may be employed in the future to bias clonal populations for higher stress tolerance to manufacturing stress, therefore increasing cell health and productivity in at-scale bioreactors.