Biology subjects

Blainey, P. C.

Publications and source records attributed to Blainey, P. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Cross-feeding reshapes interactions between antibiotic stressors through metabolic feedbacks

Stressors can combine to inhibit organismal growth or function more (synergy) or less (antagonism) strongly than expected from their individual effects, yet whether these interactions are intrinsic properties of cells or stressors, or emergent consequences of ecological interactions remains unclear. Antibiotic combinations provide a tractable model for studying stressor interactions, but have been characterized largely in bacterial monocultures. Here, we compared antibiotic stressor interactions in Escherichia coli growth in monoculture versus when cross-feeding with Salmonella enterica. Across 36 antibiotic pairs, cross-feeding frequently shifts interactions toward antagonism and away from synergy. In the sulfamethoxazole-trimethoprim pair, dual treatment increases carbon excretion by E. coli, promoting partner growth and attenuating stressor synergy through reciprocal metabolic feedback. Perturbing partner metabolite usage restores monoculture-like interaction outcomes across multiple drug pairs. Together, our results demonstrate that stressor interactions in microorganisms can emerge from ecological feedbacks mediated by metabolic excretion.

microbiology↗

bioRxiv2026

Stitch-seq: Scalable CRISPR gene expression response profiling

Single-cell profiling of genetic perturbations has expanded our ability to map causal links between genes and phenotypes; however, the high cost and technical complexity of current methods restrict systematic interrogation of dynamic cellular programs. Here, we present Stitch-seq, a high-throughput pooled functional genomics sequencing method enabling simultaneous capture of CRISPR perturbations and targeted gene and protein expression across millions of cells. Stitch-seq utilizes single-cell droplet-based overlap-extension reverse-transcription PCR reactions to physically link gene expression features of interest to perturbation identifiers without cell barcoding or extensive sequencing. We validated Stitch-seqs high fidelity using simplified models, benchmarked multi-omic Stitch-seq against single-cell RNA-sequencing in the MCF10A Epithelial-Mesenchymal Transition (EMT) model, and applied Stitch-seq to map transcriptional responses of MCF10A cells undergoing TGF-{beta}-induced EMT to perturbations across five time points. By efficiently delivering large-scale multi-omic gene expression readouts, Stitch-seq provides a powerful and accessible modality for the routine dissection of complex biological pathways.

bioengineering↗

bioRxiv2025

Bacterial peptide deformylase inhibitors induce prophages in competitors

While antibiotics mediate chemical warfare among microbes, their roles in the wild extend beyond direct growth inhibition(1). Some antibiotics have the potential to mediate interference competition by triggering a bacterial stress response that subsequently activates endogenous viruses integrated in bacterial genomes (prophages). Canonically, this activation is regulated by the SOS response upon DNA damage. Here we show that a metabolite produced by natural isolates of Vibrio ordalii circumvents the SOS response by directly triggering prophage induction in other Vibrio species, co-occurring in the same environment. While the metabolite was previously classified as a broad-spectrum antibiotic, we observe how it acts as a peptide deformylase inhibitor that specifically induces certain prophages, even when target bacterial cells carry multiple other prophages. Its biosynthetic gene cluster, or ord cluster, also encodes its own peptide deformylase (OrdE) which provides self-immunity to producer strains. Likewise, among natural Vibrio isolates that carry similar prophages, resistance against the ord metabolite was found in those that had acquired a divergent second peptide deformylase. Finally, we show that prophage induction by the ord cluster prevents slower-growing producer strains from being outcompeted by their otherwise fast-growing competitors if they carry an inducible prophage. Thus, we demonstrate how natural products play additional impactful roles in communities beyond antibiotic activity and that prophage induction serves as an interference competition strategy, sustaining community diversity.

microbiology↗

bioRxiv2024

Live-cell transcriptomics with engineered virus-like particles

The transcriptional state of a cell provides a multi-parameter representation of gene expression programs that reflect its identity and phenotype. However, current transcriptomic profiling technologies result in destruction of the biological sample, preventing direct analysis of transcriptional dynamics in the same living cells over time. Here, we developed a synthetic RNA export system called cellular self-reporting to address this fundamental technological limitation. We repurposed the murine leukemia virus retroviral protein Gag to enable diverse types of immortalized and primary mammalian cells to package cellular RNA molecules in virus-like particles (VLPs) for export into the extracellular environment. We applied self-reporting to interrogate the transcriptome-wide dynamics that occur during neuronal differentiation from induced pluripotent stem cells and detected gene expression profiles from individual live cells. Leveraging this genetically encodable approach, we expanded the capabilities of self-reporting through molecular engineering of VLP components. Pseudotyping VLPs with epitope-tagged envelope proteins enabled multiplexed selective live-cell readout of transcriptional states from heterogeneous co-cultures. Furthermore, structure-guided protein engineering of Gag fusions with human RNA binding domains improved the mRNA representation in self-reporting readouts and enabled the directed export of libraries of synthetic barcode transcripts. Taken together, this work establishes self-reporting as a facile and broadly enabling technology for live-cell, transcriptome-scale profiling of dynamic processes across diverse cell types and biological applications.

bioengineering↗

bioRxiv2024

Systematic deconstruction of myeloid cell signaling in tuberculosis granulomas reveals IFN-γ, TGF-β, and time are associated with conserved myeloid diversity

Myeloid cells are key constituents of tuberculosis (TB) granulomas. They are the major target of pathogen infection and play central roles in pathogen control, antigen presentation, adaptive immune cell recruitment, and tissue homeostasis. However, the role of myeloid cells in TB has been studied largely through ex vivo experimental approaches that do not capture the dynamic phenotypic and functional states of these cells in the disease environment. To address this gap, we used a combination of bulk and single-cell RNA sequencing (scRNA-seq), computational modeling, and imaging to define the molecular diversity of myeloid cells in granulomas from Mycobacterium tuberculosis-infected nonhuman primates. We observed an increase in myeloid cell diversity in granulomas compared to non-granulomatous lung tissue. This increased transcriptional diversity is defined by a continuum of macrophage differentiation-, metabolism-, and cytokine-regulated transcriptional programs. In vitro experimental modeling of monocyte-to-macrophage differentiation in defined cytokine environments implicates differentiation time, IFN-{gamma}, and TGF-{beta} signaling as candidate drivers of macrophage diversity. We next examined the conservation of these populations across additional experimental models of Mtb infection and found myeloid cell subsets enriched across the TB disease spectrum. To further contextualize these responses, we constructed an atlas of myeloid cells across diverse human lung pathologies, finding myeloid cell subpopulations that were similar between TB and other lung pathologies as well as subpopulations that distinguish between diseases. Collectively, this study identifies points of integration between myeloid cell biology in TB granulomas and other lung diseases that can be used for defining the signals that instruct myeloid cell behavior in TB and other diseases, as well as advance myeloid cell-targeted therapies.

immunology↗

bioRxiv2024

Classification and functional characterization of regulators of intracellular STING trafficking identified by genome-wide optical pooled screening

STING is an innate immune sensor that traffics across many cellular compartments to carry out its function of detecting cyclic di-nucleotides and triggering defense processes. Mutations in factors that regulate this process are often linked to STING-dependent human inflammatory disorders. To systematically identify factors involved in STING trafficking, we performed a genome-wide optical pooled screen and examined the impact of genetic perturbations on intracellular STING localization. Based on subcellular imaging of STING protein and trafficking markers in 45 million cells perturbed with sgRNAs, we defined 464 clusters of gene perturbations with similar cellular phenotypes. A higher-dimensional focused optical pooled screen on 262 perturbed genes which assayed 11 imaging channels identified 73 finer phenotypic clusters. In a cluster containing USE1, a protein that mediates Golgi to ER transport, we found a gene of unknown function, C19orf25. Consistent with the known role of USE1, loss of C19orf25 enhanced STING signaling. Other clusters contained subunits of the HOPS, GARP and RIC1-RGP1 complexes. We show that HOPS deficiency delayed STING degradation and consequently increased signaling. Similarly, GARP/RIC1-RGP1 loss increased STING signaling by delaying STING exit from the Golgi. Our findings demonstrate that genome-wide genotype-phenotype maps based on high-content cell imaging outperform other screening approaches, and provide a community resource for mining for factors that impact STING trafficking as well as other cellular processes observable in our dataset.

systems biology↗

bioRxiv2024

Single-cell image-based genetic screens systematically identify regulators of Ebola virus subcellular infection dynamics

Ebola virus (EBOV) is a high-consequence filovirus that gives rise to frequent epidemics with high case fatality rates and few therapeutic options. Here, we applied image-based screening of a genome-wide CRISPR library to systematically identify host cell regulators of Ebola virus infection in 39,085,093 million single cells. Measuring viral RNA and protein levels together with their localization in cells identified over 998 related host factors and provided detailed information about the role of each gene across the virus replication cycle. We trained a deep learning model on single-cell images to associate each host factor with predicted replication steps, and confirmed the predicted relationship for select host factors. Among the findings, we showed that the mitochondrial complex III subunit UQCRB is a post-entry regulator of Ebola virus RNA replication, and demonstrated that UQCRB inhibition with a small molecule reduced overall Ebola virus infection with an IC50 of 5 M. Using a random forest model, we also identified perturbations that reduced infection by disrupting the equilibrium between viral RNA and protein. One such protein, STRAP, is a spliceosome-associated factor that was found to be closely associated with VP35, a viral protein required for RNA processing. Loss of STRAP expression resulted in a reduction in full-length viral genome production and subsequent production of non-infectious virus particles. Overall, the data produced in this genome-wide high-content single-cell screen and secondary screens in additional cell lines and related filoviruses (MARV and SUDV) revealed new insights about the role of host factors in virus replication and potential new targets for therapeutic intervention.

microbiology↗

bioRxiv2024

Massively parallel combination screen reveals small molecule sensitization of antibiotic-resistant Gram-negative ESKAPE pathogens

Antibiotic resistance, especially in multidrug-resistant ESKAPE pathogens, remains a worldwide problem. Combination antimicrobial therapies may be an important strategy to overcome resistance and broaden the spectrum of existing antibiotics. However, this strategy is limited by the ability to efficiently screen large combinatorial chemical spaces. Here, we deployed a high-throughput combinatorial screening platform, DropArray, to evaluate the interactions of over 30,000 compounds with up to 22 antibiotics and 6 strains of Gram-negative ESKAPE pathogens, totaling to over 1.3 million unique strain-antibiotic-compound combinations. In this dataset, compounds more frequently exhibited synergy with known antibiotics than single-agent activity. We identified a compound, P2-56, and developed a more potent analog, P2-56-3, which potentiated rifampin (RIF) activity against Acinetobacter baumannii and Klebsiella pneumoniae. Using phenotypic assays, we showed P2-56-3 disrupts the outer membrane of A. baumannii. To identify pathways involved in the mechanism of synergy between P2-56-3 and RIF, we performed genetic screens in A. baumannii. CRISPRi-induced partial depletion of lipooligosaccharide transport genes (lptA-D, lptFG) resulted in hypersensitivity to P2-56-3/RIF treatment, demonstrating the genetic dependency of P2-56-3 activity and RIF sensitization on lpt genes in A. baumannii. Consistent with outer membrane homeostasis being an important determinant of P2-56-3/RIF tolerance, knockout of maintenance of lipid asymmetry complex genes and overexpression of certain resistance-nodulation-division efflux pumps - a phenotype associated with multidrug-resistance - resulted in hypersensitivity to P2-56-3. These findings demonstrate the immense scale of phenotypic antibiotic combination screens using DropArray and the potential for such approaches to discover new small molecule synergies against multidrug-resistant ESKAPE strains. Significance StatementThere is an unmet need for new antibiotic therapies effective against the multidrug-resistant, Gram-negative ESKAPE pathogens. Combination therapies have the potential to overcome resistance and broaden the spectrum of existing antibiotics. In this study, we use DropArray, a massively parallel combinatorial screening tool, to assay more than 1.3 million combinations of small molecules against the Gram-negative ESKAPE pathogens, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. We discovered a synthetic small molecule potentiator, P2-56, of the antibiotic rifampin effective in A. baumannii and K. pneumoniae. We generated P2-56-3, a more potent derivative of P2-56, and found that it likely potentiates rifampin by compromising the outer membrane integrity. Our study demonstrates a high-throughput strategy for identifying antibiotic potentiators against multidrug-resistant bacteria.

microbiology↗

bioRxiv2024

CROPseq-multi: a versatile solution for multiplexed perturbation and decoding in pooled CRISPR screens

Forward genetic screens seek to dissect complex biological systems by systematically perturbing genetic elements and observing the resulting phenotypes. While standard screening methodologies introduce individual perturbations, multiplexing perturbations improves the performance of single-target screens and enables combinatorial screens for the study of genetic interactions. Current tools for multiplexing perturbations are limited by technical challenges and do not offer compatibility across diverse screening methodologies, including enrichment, single-cell sequencing, and optical pooled screens. Here, we report the development of CROPseq-multi (CSM), a CROPseq1-inspired lentiviral system to multiplex Streptococcus pyogenes (Sp) Cas9-based perturbations with versatile readout compatibility and high performance for both perturbation and barcode identification. CSM has equivalent per-guide activity to CROPseq and low lentiviral recombination frequencies. Dual-guide CSM libraries are constructed in a single, facile molecular cloning step that facilitates the use of unique molecular identifiers. CSM is compatible with enrichment screening methodologies, single-cell RNA-sequencing readouts, and optical pooled screens. For optical pooled screens, an optimized and multiplexed in situ detection protocol improves barcode counts 10-fold (for mRNA detection), enables detection of recombination events, and reduces the number of sequencing cycles required for decoding by 3-fold relative to CROPseq. CROPseq-multi-v2 (CSMv2) adds compatibility for detection methods based on T7 RNA polymerase in vitro transcription2-5. CSM provides a single system for CRISPR screens that is compatible with individual and combinatorial perturbations, diverse SpCas9-based perturbation technologies, and multiple high-content, single-cell phenotypic readouts.

genomics↗

bioRxiv2024

De novo mutations mediate phenotypic switching in an opportunistic human lung pathogen

Bacteria evolving within human hosts encounter selective tradeoffs that render mutations adaptive in one context and deleterious in another. Here, we report that the cystic fibrosis-associated pathogen Burkholderia dolosa overcomes in-human selective tradeoffs by acquiring successive point mutations that alternate phenotypes. We sequenced the whole genomes of 931 respiratory isolates from two recently infected patients and an epidemiologically-linked, chronically-infected patient. These isolates are contextualized using 112 historical genomes from the same outbreak strain. Within both newly infected patients, diverse parallel mutations that disrupt O-antigen expression quickly arose, comprising 29% and 63% of their B. dolosa communities by 3 years. The selection for loss of O-antigen starkly contrasts with our previous observation of parallel O-antigen-restoring mutations after many years of chronic infection in the historical outbreak. Experimental characterization revealed that O-antigen loss increases uptake in immune cells while decreasing competitiveness in the mouse lung. We propose that the balance of these pressures, and thus whether O-antigen expression is advantageous, depends on tissue localization and infection duration. These results suggest that mutation-driven alternation during infection may be more frequent than appreciated and is underestimated without dense temporal sampling.

microbiology↗

bioRxiv2023

Vaginal Lactobacillus fatty acid response mechanisms reveal a novel strategy for bacterial vaginosis treatment

Bacterial vaginosis (BV), a common syndrome characterized by Lactobacillus-deficient vaginal microbiota, is associated with adverse health outcomes. BV often recurs after standard antibiotic therapy in part because antibiotics promote microbiota dominance by Lactobacillus iners instead of Lactobacillus crispatus, which has more beneficial health associations. Strategies to promote L. crispatus and inhibit L. iners are thus needed. We show that oleic acid (OA) and similar long-chain fatty acids simultaneously inhibit L. iners and enhance L. crispatus growth. These phenotypes require OA-inducible genes conserved in L. crispatus and related species, including an oleate hydratase (ohyA) and putative fatty acid efflux pump (farE). FarE mediates OA resistance, while OhyA is robustly active in the human vaginal microbiota and sequesters OA in a derivative form that only ohyA-harboring organisms can exploit. Finally, OA promotes L. crispatus dominance more effectively than antibiotics in an in vitro model of BV, suggesting a novel approach for treatment.

microbiology↗

bioRxiv2023

KatG catalase deficiency confers bedaquiline hyper-susceptibility to isoniazid resistant Mycobacterium tuberculosis

Multidrug-resistant tuberculosis (MDR-TB) is a growing source of global mortality and threatens global control of tuberculosis (TB) disease. The diarylquinoline bedaquiline (BDQ) recently emerged as a highly efficacious drug against MDR-TB, defined as resistance to the first-line drugs isoniazid (INH) and rifampin. INH resistance is primarily caused by loss-of-function mutations in the catalase KatG, but mechanisms underlying BDQs efficacy against MDR-TB remain unknown. Here we employ a systems biology approach to investigate BDQ hyper-susceptibility in INH-resistant Mycobacterium tuberculosis. We found hyper-susceptibility to BDQ in INH-resistant cells is due to several physiological changes induced by KatG deficiency, including increased susceptibility to reactive oxygen species and DNA damage, remodeling of transcriptional programs, and metabolic repression of folate biosynthesis. We demonstrate BDQ hyper-susceptibility is common in INH-resistant clinical isolates. Collectively, these results highlight how altered bacterial physiology can impact drug efficacy in drug-resistant bacteria.

microbiology↗

bioRxiv2023

A genome-wide atlas of human cell morphology

A key challenge of the modern genomics era is developing data-driven representations of gene function. Here, we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-scale genotype-phenotype maps comprising >20,000 single-gene CRISPR-Cas9-based knockout experiments in >30 million cells. Our optical pooled cell profiling approach (PERISCOPE) combines a de-stainable high-dimensional phenotyping panel (based on Cell Painting1,2) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries. This approach provides high-dimensional phenotypic profiles of individual cells, while simultaneously enabling interrogation of subcellular processes. Our atlas reconstructs known pathways and protein-protein interaction networks, identifies culture media-specific responses to gene knockout, and clusters thousands of human genes by phenotypic similarity. Using this atlas, we identify the poorly-characterized disease-associated transmembrane protein TMEM251/LYSET as a Golgi-resident protein essential for mannose-6-phosphate-dependent trafficking of lysosomal enzymes, showing the power of these representations. In sum, our atlas and screening technology represent a rich and accessible resource for connecting genes to cellular functions at scale.

genomics↗

bioRxiv2023

Compressed phenotypic screens for complex multicellular models and high-content assays

High-throughput phenotypic screens leveraging biochemical perturbations, high-content readouts, and complex multicellular models could advance therapeutic discovery yet remain constrained by limitations of scale. To address this, we establish a method for compressing screens by pooling perturbations followed by computational deconvolution. Conducting controlled benchmarks with a highly bioactive small molecule library and a high-content imaging readout, we demonstrate increased efficiency for compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening to examine transcriptional responses of patient-derived pancreatic cancer organoids to a library of tumor-microenvironment (TME)-nominated recombinant protein ligands. Using single-cell RNA-seq as a readout, we uncover reproducible phenotypic shifts induced by ligands that correlate with clinical features in larger datasets and are distinct from reference signatures available in public databases. In sum, our approach enables phenotypic screens that interrogate complex multicellular models with rich phenotypic readouts to advance translatable drug discovery as well as basic biology.

systems biology↗

bioRxiv2021

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel pre-amplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a proof of principle system for use with stabilized reagents and a simple workflow with optical readout using a cell phone camera, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing. Significance StatementIn this paper, we use a novel primer design method combined with droplet-based CRISPR Cas13 detection to distinguish 52 clinically relevant bacterial pathogens in a single assay. We also apply the method to detect and distinguish a panel of major antibiotic resistance genes, which is of critical importance in this era of rising antibiotic resistance. Finally, we make key advances towards making our diagnostic assay deployable at the point-of-care, with a simplified emulsion-free assay process that uses mobile phone camera for detection and reduces infrastructure/skilled labor requirements.

microbiology↗

bioRxiv2021

High-throughput RNA isoform sequencing using programmable cDNA concatenation

Alternative splicing is a core biological process that enables profound and essential diversification of gene function. Short-read RNA sequencing approaches fail to resolve RNA isoforms and therefore primarily enable gene expression measurements - an isoform unaware representation of the transcriptome. Conversely, full-length RNA sequencing using long-read technologies are able to capture complete transcript isoforms, but their utility is deeply constrained due to throughput limitations. Here, we introduce MAS-ISO-seq, a technique for programmably concatenating cDNAs into single molecules optimal for long-read sequencing, boosting the throughput >15 fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. We validated unambiguous isoform assignment with MAS-ISO-seq using a synthetic RNA isoform library and applied this approach to single-cell RNA sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor. Methods such as MAS-ISO-seq will drive discovery of novel isoforms and the transition from gene expression to transcript isoform expression analyses.

genetics↗

bioRxiv2020

Efficient design of maximally active and specific nucleic acid diagnostics for thousands of viruses

Diagnostics, particularly for rapidly evolving viruses, stand to benefit from a principled, measurement-driven design that harnesses machine learning and vast genomic data--yet the capability for such design has not been previously built. Here, we develop and extensively validate an approach to designing viral diagnostics that applies a learned model within a combinatorial optimization framework. Concentrating on CRISPR-based diagnostics, we screen a library of 19,209 diagnostic-target pairs and train a deep neural network that predicts, from RNA sequence alone, diagnostic signal better than contemporary techniques. Our model then makes it possible to design assays that are maximally sensitive over the spectrum of a viruss genomic variation. We introduce ADAPT (https://adapt.guide), a system for fully-automated design, and use ADAPT to design optimal diagnostics for the 1,933 vertebrate-infecting viral species within 2 hours for most species and 24 hours for all but 3. We experimentally show ADAPTs designs are sensitive and specific down to the lineage level, including against viruses that pose challenges involving genomic variation and specificity. ADAPTs designs exhibit significantly higher fluorescence and permit lower limits of detection, across a viruss entire variation, than the outputs of standard design techniques. Our model-based optimization strategy has applications broadly to viral nucleic acid diagnostics and other sequence-based technologies, and, paired with clinical validation, could enable a critically-needed, proactive resource of assays for surveilling and responding to pathogens.

genomics↗

bioRxiv2020

Induction of a regulatory myeloid program in bacterial sepsis and severe COVID-19

A recent estimate suggests that one in five deaths globally are associated with sepsis1. To date, no targeted treatment is available for this syndrome, likely due to substantial patient heterogeneity2,3 and our lack of insight into sepsis immunopathology4. These issues are highlighted by the current COVID-19 pandemic, wherein many clinical manifestations of severe SARS-CoV-2 infection parallel bacterial sepsis5-8. We previously reported an expanded CD14+ monocyte state, MS1, in patients with bacterial sepsis or non-infectious critical illness, and validated its expansion in sepsis across thousands of patients using public transcriptomic data9. Despite its marked expansion in the circulation of bacterial sepsis patients, its relevance to viral sepsis and association with disease outcomes have not been examined. In addition, the ontogeny and function of this monocyte state remain poorly characterized. Using public transcriptomic data, we show that the expression of the MS1 program is associated with sepsis mortality and is up-regulated in monocytes from patients with severe COVID-19. We found that blood plasma from bacterial sepsis or COVID-19 patients with severe disease induces emergency myelopoiesis and expression of the MS1 program, which are dependent on the cytokines IL-6 and IL-10. Finally, we demonstrate that MS1 cells are broadly immunosuppressive, similar to monocytic myeloid-derived suppressor cells (MDSCs), and have decreased responsiveness to stimulation. Our findings highlight the utility of regulatory myeloid cells in sepsis prognosis, and the role of systemic cytokines in inducing emergency myelopoiesis during severe bacterial and SARS-CoV-2 infections.

immunology↗