Biology subjects

Subramanian, A.

Publications and source records attributed to Subramanian, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Predicting Neoantigen Immunogenicity from In Vivo Immune Editing

Neoantigen immunogenicity prediction is fundamental to personalized cancer vaccines, tumor-infiltrating lymphocyte (TIL) therapy, and TCR-T cell engineering. Existing computational predictors rely primarily on in-vitro correlates of peptide presentation or models trained against assay-based reactivity, and they are typically validated within a single therapeutic setting. We reasoned that the most direct evidence of neoantigen immunogenicity is longitudinal in-vivo elimination: under immune checkpoint blockade (ICB), subclones bearing recognized neoantigens are selectively depleted over time. Here, we present the Neoantigen Elimination Model (NEMo), a two-compartment (CD8 and CD4) machine learning classifier trained on the in-vivo editing (IVE) of neoantigens across serially sequenced, ICB-treated tumors. By using mechanistically inspired NeoPrecis features designed to capture determinants of immunogenicity beyond MHC binding affinity, NEMo recovered assay-confirmed immunogenic neoantigens across four independent, unseen clinical settings -- pre-existing immunogenicity screening, personalized cancer vaccines, TIL therapy, and a radiotherapy +/- ICB ctDNA cohort -- and stratified progression-free survival more strongly than ELISPOT-confirmed reactivity. The editing signal further revealed an immune-evasion architecture in which oncogenic drivers and neoantigens restricted to lost or silenced HLA alleles are systematically spared from editing.

cancer biology↗

bioRxiv2026

An Integrated Atlas of the Human Kidney Spanning Health and Diseases

The human kidney contains highly specialized cell populations. Despite numerous single-cell and single-nucleus transcriptomics studies, differences in cohorts, technologies, analytical pipelines, and annotation frameworks have limited the ability to define consensus kidney cell states, identify disease-associated populations and interpret kidney disease genetic susceptibility. Here, we assembled 18 human kidney single-cell and single-nucleus RNA-sequencing datasets spanning 232 donors and five major disease contexts into a uniformly processed and computationally integrated Human Kidney Cell Atlas (HKCA), comprising over one million high-quality cells (816,895) and nuclei (215,308). The HKCA resolves 63 cell types and 120 harmonized cell states, including rare epithelial and stromal populations associated with kidney diseases . Integration with spatial transcriptomics, intercellular communication networks, and human genetic association data further defined the anatomical context and disease relevance of these populations. The HKCA also provides a framework for automated annotation of independent kidney human and mouse datasets. Together, the HKCA establishes a comprehensive reference for human kidney biology, enabling disease interpretation and genetic risk localization at cellular resolution.

genomics↗

bioRxiv2026

IRE1 drives a homeostatic response to reduced protein influx into the endoplasmic reticulum

IRE1, alongside ATF6 and PERK, orchestrates the Unfolded Protein Response, a network of signaling pathways that maintains endoplasmic reticulum (ER) homeostasis. Two modes of IRE1 activation are known: i) in response to an accumulation of unfolded proteins in the ER lumen and ii) in response to compositional changes to the ER membrane that alter its physical properties. Here we identify a third, independent mode of IRE1 activation: ER co-translational translocation deficits activate IRE1 through a mechanism that relies on the release of IRE1 molecules from unoccupied translocons. We define this mechanism as TRES for "TRanslocon Engagement Surveillance". TRES leads to spontaneous activation of IRE1 and bypasses its unfolded protein- and ER membrane composition-sensing functions. Inhibiting translation initiation similarly activates IRE1 by TRES, as it leads to a decline in ER protein import, thus linking the Integrated Stress Response to IRE1 signaling. TRES drives IRE1 activation without activating ATF6 or PERK, resulting in a distinct gene expression program that feeds back by boosting the co-translational translocation machinery to rebalance the ER protein load. Our findings thus demonstrate that monitoring and adjusting the rates of protein translocation are critical for maintaining ER homeostasis.

cell biology↗

bioRxiv2026

Object recognition along the ventral stream: effects of visual noise

How does the visual system recognize objects in natural environments? Here, we investigate the neural computations underlying robust object recognition along the ventral stream. We adapted psychophysical critical-band masking to fMRI, measuring BOLD responses along the ventral stream to natural images perturbed by bandpass noise. We found that, along this stream, the overall BOLD response to noise alone is sensitive to an increasingly wide range of stimulus spatial frequency, from 2 octaves in V1 to 5 octaves in ventral temporal cortex (VTC). However, when we assess the effect of the same noise on the accuracy of decoding scene images from the BOLD response, we obtain a different result: Recognition bandwidth is conserved along the ventral stream at about 2 octaves, close to the 1.5-octave behavioral channel. Though the recognition band is conserved, its noise tolerance increases steadily along the ventral stream, approaching behavioral levels in VTC. These findings suggest that V1 sets the bandwidth of the object-recognition channel, while downstream areas progressively denoise the signal, establishing the channels noise tolerance. This biological architecture--early channel isolation followed by successive denoising--may explain why human vision remains more robust than current machine vision.

neuroscience↗

bioRxiv2026

NAViFluX: a visualization-centric platform for interactive analysis, refinement and design of genome-scale metabolic networks

Genome-scale metabolic network (GSMN) models are rigorously curated, cellular-level representations of metabolism that enable flux-based metabolite fate discovery, metabolic engineering, drug target identification and context-specific multi-omics integration. However, the inherent complexity of model architectures, need for programming skills and limited visualization support restrict their broader applicability. Existing tools focus on visualization and analyses separately, necessitating tool-specific format conversions, offer either topology or flux analyses options exclusively, lack intuitive pathway-specific visualizations, database-integrated model refinement, pathway enrichment and large-scale perturbation analyses. Here, we present NAViFluX (metabolic Network Analysis and Visualization of Flux), a visualization-centric, web browser-based environment that unifies GSMN exploration through native pathway / subsystem map generation using various layouts; interactive refinement through addition of reactions from KEGG / BiGG, amending constraints, pathway merging; and modules for flux computations, topology, functional enrichment. Instead of treating visualization as a post hoc step, NAViFluX performs all actions within network views, enabling users to make decisions directly from visually interpretable subnetworks. Using three Escherichia coli case studies, NAViFluX is shown to characterize nutrient-specific metabolic adaptations, improve metabolic gene essentiality predictions, provide mechanistic insight into synthetic lethality and facilitate the design of an optimized carbon-fixing metabolic state, thereby democratizing GSMNs for biologically meaningful applications. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/697453v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@9fff20org.highwire.dtl.DTLVardef@26b947org.highwire.dtl.DTLVardef@4e0f7aorg.highwire.dtl.DTLVardef@da307d_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

An induced pluripotent stem cell-based chemical genetic approach for studying spinal muscular atrophy

Spinal muscular atrophy (SMA) is a genetic disease characterized by degeneration of spinal cord motor neurons and neuromuscular junctions. Despite recent development in therapies for SMA, treatment efficacy largely relies on administration of drugs early in disease progression and is impacted by underlying patient genetics. Drug discovery for other diseases of the central nervous system (CNS) has also been hindered by heterogeneity in patient genetics and clinical presentations, as well as the need for early intervention. To address these hurdles, we utilized a chemical genetic-based screening approach to adapt the Connectivity Map (CMAP)/L1000 platform to study SMA. To do this, we differentiated moderate and severe SMA patient-specific induced pluripotent stem cells into neuronal cells utilizing a forward programming differentiation protocol, exposed each to 360 neuroactive or CNS disease-related compounds, and interrogated resulting changes in expression of >400 neural genes in a platform we term CMAPneuro. In doing so, we generated 4,559 transcriptional profiles identifying stimuli that modulate gene expression differences across SMA neurons. Finally, we make these data queryable, allowing the research community to 1.) identify CNS disease-related perturbagens that mimic or reverse differentially expressed genes, or 2.) explore the transcriptional response of a given perturbation in diverse SMA neuronal cells.

neuroscience↗

bioRxiv2025

Trehalose metabolism regulates transcriptional control of muscle development in lepidopteran insects

The connection between trehalose metabolism and insect muscle development has long been unclear. Here we demonstrate that trehalose-derived glucose flux is essential for sustaining glycolysis and maintaining cellular energetics during metamorphosis in Helicoverpa armigera. Disruption of trehalose synthesis through silencing of trehalose 6-phosphate synthase/phosphatase (TPS/TPP) or paramyosin (Prm) produced defective eclosion and alike fragmented muscle fibers. Metabolic profiling revealed broad depletion of glycolytic intermediates and cofactors consistent with elevated AMP and activation of energy-stress signalling. Transcriptome analysis also showed downregulation of the transcription factor E2F/Dp, along with reduced expression of cyclin/CDK components, indicative of cell cycle checkpoint dysregulation. E2F/Dp repression resulted in lower expression of Mef2, Prm, MHC, and other sarcomeric components, causing defective muscle development and weakened muscle architecture. Gene set enrichment analysis, gene regulatory network and promotor binding analysis confirmed E2F binding motifs within promoters of trehalose metabolism and myogenic genes, suggesting a potential metabolic-transcriptional connection. Furthermore, dietary trehalose supplementation partially rescued metabolic depletion and restored expression of E2F targets in TPS/TPP- and E2F/Dp-silenced insects. Collectively, our findings establish trehalose metabolism as a metabolic regulator that couples energy homeostasis to cell-cycle transcriptional control and muscle development.

developmental biology↗

bioRxiv2025

Allosteric Disordering of eIF2B Regulates the Integrated Stress Response

The ternary complex (TC), composed of translation initiation factor eIF2, GTP, and initiator methionyl tRNA, delivers the first amino acid to the ribosome to initiate protein synthesis. The activity of the decameric eukaryotic initiation factor 2B complex (eIF2B) initiates TC assembly by catalyzing GDP to GTP exchange on eIF2, thereby setting the TC levels in the cell. Stress-induced phosphorylation converts eIF2 from the substrate of the GDP/GTP exchange reaction into an inhibitor (eIF2-P) of eIF2B. This conversion reduces the cells TC levels and induces the widespread reprogramming of translation known as the Integrated Stress Response (ISR). Here, we chart an allosteric axis running through eIF2B, revealing the importance of a protrusive -helix in its {beta}-subunit, the latch-helix, that locks onto the -subunit to induce eIF2B activity. eIF2-P binding unhooks the latch-helix, opening eIF2B, which inhibits its GDP/GTP exchange activity. Distinct viral proteins have convergently evolved to bind to eIF2B and stabilize the latch-helix-bound active state. Using these insights, we generated ISR-ACTivating compounds, ISRACTs, that stabilize eIF2B in its inhibited, unlatched state. Our study thus highlights how state-transitions in eIF2B are regulated via long-range allostery.

biochemistry↗

bioRxiv2025

PANoptosis, a combination of inflammatory cell death mechanisms, induced 1 by Ophiobolin A in breast cancer cell lines

An unmet challenge in managing breast cancer is treatment failure due to resistance to apoptosis-inducing chemotherapies. Thus, it is important to identify novel non-apoptotic therapeutic agents. Several non-apoptotic programmed cell death pathways utilize specific cellular signaling events to trigger lytic and pro-inflammatory cell death. PANoptosis, which encompasses pyroptosis, apoptosis and necroptosis, is of paramount importance in the regulation of cell death and immune responses. Our study illustrates that ophiobolin A (OpA) is an anti-cancer agent that triggers lytic cell death in breast cancer cells, including triple-negative breast cancer (TNBC), via a mechanism dependent on RIPK1. This study reveals that OpA induces typical pyroptosis-like characteristics, including cellular swelling, plasma membrane rupture, GSDMD cleavage and release of cytokines in breast cancer cells. The involvement of caspase 3, RIPK1, and GSDMD suggests that PANoptosis is activated upon OpA treatment in breast cancer. The induction of pro-inflammatory cell death suggests potential applications for OpA in cancer treatment.

cancer biology↗

bioRxiv2025

SCAN-ACT: Adoptive T Cell Therapy Target Discovery Through Single-Cell Transcriptomics

The FDA approval of T cell receptor-engineered T cells (TCR-T) for synovial sarcoma demonstrates the potential for adoptive T cell therapies (ACTs) in solid tumors. However, the paucity of tumor-specific targets without expression in normal tissues remains a major bottleneck, especially in rare cancer subtypes. Here, we present a comprehensive computational pipeline called SCAN-ACT that leverages single cell RNA sequencing and multi-omics data from tumor and normal tissues to nominate and prioritize targets for both chimeric antigen receptor (CAR)- and TCR-T cells. For surface membrane targets, SCAN-ACT proposes target pairs for bispecific Boolean logic-gated CAR T cells. For peptide-MHC targets, SCAN-ACT proposes intracellular peptides bound to a diverse set of human leukocyte antigens. We applied the SCAN-ACT pipeline to soft tissue sarcoma (STS), analyzing 986,749 single cells to identify and prioritize 395 monospecific CAR-T targets, 14,192 bispecific CAR-T targets, and 5,020 peptide-MHC targets for TCR-T cells. Selected targets were validated experimentally by protein expression and for peptide-MHC binding. Proposed targets and target pairs reflected the mesenchymal, neuronal, and hematopoietic ontogeny of STS. This work provides a robust data repository along with a web-based and user-friendly set of analysis tools to accelerate ACT development for solid tumors.

cancer biology↗

bioRxiv2024

Sex differences and immune correlates of Long COVID development, persistence, and resolution

Sex differences have been observed in acute COVID-19 and Long COVID (LC) outcomes, with greater disease severity and mortality during acute infection in males and a greater proportion of females developing LC. We hypothesized that sex-specific immune dysregulation contributes to the pathogenesis of LC. To investigate the immunologic underpinnings of LC development and persistence, we used single-cell transcriptomics, single-cell proteomics, and plasma proteomics on blood samples obtained during acute SARS-CoV-2 infection and at 3 and 12 months post-infection in a cohort of 45 patients who either developed LC or recovered. Several sex-specific immune pathways were associated with LC. Specifically, males who would develop LC at 3 months had widespread increases in TGF-{beta} signaling during acute infection in proliferating NK cells. Females who would develop LC demonstrated increased expression of XIST, an RNA gene implicated in autoimmunity, and increased IL1 signaling in monocytes at 12 months post infection. Several immune features of LC were also conserved across sexes. Both males and females with LC had reduced co-stimulatory signaling from monocytes and broad upregulation of NF-{kappa}B transcription factors. In both sexes, those with persistent LC demonstrated increased LAG3, a marker of T cell exhaustion, reduced ETS1 transcription factor expression across lymphocyte subsets, and elevated intracellular IL-4 levels in T cell subsets, suggesting that ETS1 alterations may drive an aberrantly elevated Th2-like response in LC. Altogether, this study describes multiple innate and adaptive immune correlates of LC, some of which differ by sex, and offers insights toward the pursuit of tailored therapeutics. One Sentence SummaryThis multi-omic analysis of Long COVID reveals sex differences and immune correlates of Long COVID development, persistence, and resolution.

immunology↗

bioRxiv2024

A prostate cancer gastrointestinal transcriptional phenotype may be associated with diminished response to AR-targeted therapy

BackgroundProstate cancer is a heterogenous disease, but once it becomes metastatic it eventually becomes treatment resistant. One mechanism of resistance to AR-targeting therapy is lineage plasticity, where the tumor undergoes a transformation to an AR-indifferent phenotype, most studied in the context of neuroendocrine prostate cancer (NEPC). However, activation of additional de- or trans-differentiation programs, including a gastrointestinal (GI) gene expression program, has been suggested as an alternative method of resistance. In this study, we explored the previously identified GI prostate cancer phenotype (PCa-GI) in a large cohort of metastatic castration-resistant prostate cancer (mCRPC) patient biopsy samples. MethodsWe analyzed a dataset of 634 mCRPC samples with batch effect corrected gene expression data from the West Coast Dream Team (WCDT), the East Coast Dream Team (ECDT), the Fred Hutchinson Cancer Research Center (FHCRC) and the Weill Cornell Medical center (WCM). Survival data was available from the WCDT and ECDT cohorts. We calculated a gene expression GI score using the sum of z-scores of genes from a published set of PCa-GI-defining genes (N=38). Survival analysis was performed using the Kaplan-Meier method and Cox proportional hazards regression with endpoint overall survival from time of biopsy to death of any cause. ResultsWe found that the PCa-GI score had a bimodal distribution, identifying a distinct set of tumors with an activated GI expression pattern. Approximately 35% of samples were classified as PCa-GI high, which was concordant with prior reports. Liver metastases had the highest median score but after excluding liver samples, 29% of the remaining samples were still classified as PCa-GI high, suggesting a distinct phenotype not exclusive to liver metastases. No correlation was observed between GI score and proliferation, AR signaling, or NEPC scores. Furthermore, the PCa-GI score was not associated with genomic alterations in AR, FOXA1, RB1, TP53 or PTEN. However, tumors with MYC amplifications showed significantly higher GI scores (p=0.0001). Patients with PCa-GI tumors had a shorter survival (HR=1.5 [1.1-2.1], p=0.02), but this result was not significant after adjusting for the liver as metastatic site (HR=1.2 [0.82-1.7], p=0.35). Patients with PCa-GI low samples had a better outcome after androgen receptor signaling inhibitors (ASI, abiraterone or enzalutamide) than other therapies (HR=0.37 [0.22-0.61], p=0.0001) while the benefit of ASI was smaller and non-significant for PCa-GI high samples (HR=0.55 [0.29-1.1], p=0.07). A differential pathway analysis identified FOXA2 signaling to be upregulated PCa-GI high tumors (FDR = 3.7 x 10-13). ConclusionsThe PCa-GI phenotype is prevalent in clinical mCRPC samples and may represent a distinct biological entity. PCa-GI tumors may respond less to ASI and could offer a strategy to study novel therapeutic targets.

cancer biology↗

bioRxiv2024

Enhancing radiotherapy response via intratumoral injection of the TLR9 agonist CpG to stimulate CD8 T cells in an autochthonous mouse model of sarcoma

Radiation therapy is frequently used to treat cancers including soft tissue sarcomas. Prior studies established that the toll-like receptor 9 (TLR9) agonist cytosine-phosphate-guanine oligodeoxynucleotide (CpG) enhances the response to radiation therapy (RT) in transplanted tumors, but the mechanism(s) remain unclear. Here, we used CRISPR/Cas9 and the chemical carcinogen 3-methylcholanthrene (MCA) to generate autochthonous soft tissue sarcomas with high tumor mutation burden. Treatment with a single fraction of 20 Gy RT and two doses of CpG significantly enhanced tumor response, which was abrogated by genetic or immunodepletion of CD8+ T cells. To characterize the immune response to RT + CpG, we performed bulk RNA-seq, single-cell RNA-seq, and mass cytometry. Sarcomas treated with 20 Gy and CpG demonstrated increased CD8 T cells expressing markers associated with activation and proliferation, such as Granzyme B, Ki-67, and interferon-{gamma}. CpG + RT also upregulated antigen presentation pathways on myeloid cells. Furthermore, in sarcomas treated with CpG + RT, TCR clonality analysis suggests an increase in clonal T-cell dominance. Collectively, these findings demonstrate that RT + CpG significantly delays tumor growth in a CD8 T cell-dependent manner. These results provide a strong rationale for clinical trials evaluating CpG or other TLR9 agonists with RT in patients with soft tissue sarcoma.

cancer biology↗

bioRxiv2023

Comparing neural models using their perceptual discriminability predictions

Internal representations are not uniquely identifiable from perceptual measurements: different representations can generate identical perceptual predictions, and similar representations may predict dissimilar percepts. Here, we generalize a previous method ("Eigendistortions" - Berardino et al., 2017) to enable comparison of models based on their metric tensors, which can be verified perceptually. Metric tensors characterize sensitivity to stimulus perturbations, reflecting both the geometric and stochastic properties of the representation, and providing an explicit prediction of perceptual discriminability. Brute force comparison of model-predicted metric tensors would require estimation of human perceptual thresholds along an infeasibly large set of stimulus directions. To circumvent this "perceptual curse of dimensionality", we compute and measure discrimination capabilities for a small set of most-informative perturbations, reducing the measurement cost from thousands of hours (a conservative estimate) to a single trial. We show that this single measurement, made for a variety of different test stimuli, is sufficient to differentiate models, select models that better match human perception, or generate new models that combine the advantages of existing models. We demonstrate the power of this method in comparison of (1) two models for trichromatic color representation, with differing internal noise; and (2) two autoencoders trained with different regularizers.

neuroscience↗

bioRxiv2023

TIM-4 identifies effector B cells expressing an IL-23-driven proinflammatory cytokine module that promotes immune responses

B cells can express pro-inflammatory cytokines that promote a wide variety of immune responses. Here we show that B cells expressing the phosphatidylserine receptor TIM-4, preferentially express IL-17A, as well as IL-22, IL-6, IL-1{beta}, and GM-CSF - a pattern of cytokines reminiscent of pathogenic Th17 cells. Expression of this proinflammatory module requires IL-23R signaling and selective expression of ROR{gamma}t by TIM-4+ B cells. TIM-4+ B cell-derived-IL-17A not only enhances the severity of experimental autoimmune encephalomyelitis (EAE) and promotes allograft rejection but also acts in an autocrine manner to prevent their conversion into IL-10-expressing B cells with regulatory function. Thus, IL-17A acts as an inflammatory mediator and enforces the proinflammatory activity of TIM-4+ B cells. Moreover, TIM-4 serves as a broad marker for ROR{gamma}t-expressing effector B cells (Beff). These findings allow further study of the signals regulating Beff differentiation and effector molecule expression.

immunology↗

bioRxiv2022

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

genomics↗

bioRxiv2022

Transcriptome profiling of tendon fibroblasts at the onset of embryonic muscle contraction reveals novel force-responsive genes

Mechanical forces play a critical role in tendon development and function, influencing cell behavior through mechanotransduction signaling pathways and subsequent extracellular matrix (ECM) remodeling. Here we investigate the molecular mechanisms by which tenocytes in developing zebrafish embryos respond to muscle contraction forces during the onset of swimming and cranial muscle activity. Using genome-wide bulk RNA sequencing of FAC-sorted tenocytes we identify novel tenocyte markers and genes involved in tendon mechanotransduction. Embryonic tendons show dramatic changes in expression of Matrix Remodeling Associated 5b (mxra5b), Matrilin 1 (matn1), and the transcription factor Kruppel-like factor 2a (klf2a), as muscles start to contract. Using embryos paralyzed either by loss of muscle contractility or neuromuscular stimulation we confirm that muscle contractile forces influence the spatial and temporal expression patterns of all three genes. Quantification of these gene expression changes across tenocytes at multiple tendon entheses and myotendinous junctions reveals that their responses depend on force intensity, duration and tissue stiffness. These force-dependent feedback mechanisms in tendons, particularly in the ECM, have important implications for improved treatments of tendon injuries and atrophy.

developmental biology↗

bioRxiv2022

Proteome capacity constraints favor respiratory ATP generation

Cells face competing metabolic demands. These include efficient use of both limited substrates and limited proteome capacity, as well as flexibility to deal with different environments. Flexibility requires spare enzyme capacity, which is proteome inefficient. ATP generation can occur via fermentation or respiration. Fermentation is much less substrate-efficient, but often assumed to be more proteome efficient 1-3, thereby favoring fast-growing cells engaging in aerobic glycolysis 4-8. Here, however, we show that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. Instead, aerobic glycolysis arises from cells maintaining the flexibility to grow also anaerobically. These conclusions emerged from an unbiased assessment of metabolic regulatory mechanisms, integrating quantitative metabolomics, proteomics, and fluxomics, of two budding yeasts, Saccharomyces cerevisiae and Issatchenkia orientalis, the former more fermentative and the latter respiratory. Their energy pathway usage is largely explained by differences in proteome allocation. Each organisms proteome allocation is remarkably stable across environmental conditions, with metabolic fluxes predominantly regulated at the level of metabolite concentrations. This leaves extensive spare biosynthetic capacity during slow growth and spare capacity of their preferred bioenergetic machinery when it is not essential. The greater proteome-efficiency of respiration is also observed in mammals, with aerobic glycolysis occurring in yeast or mammalian cells that maintain a fermentation-capable proteome conducive to both aerobic and anaerobic growth.

systems biology↗