Biology subjects

Zhernovkov, V.

Publications and source records attributed to Zhernovkov, V..

12 recordsLinked to original sources

bioRxiv2026

IFN and IFN mimetics prevent IFN-I-mediated TB susceptibility by regulating iron metabolism and lipid peroxidation

Type I interferons (IFN-I) and IFN{gamma} exert divergent effects during tuberculosis, but the mechanisms that determine whether macrophage activation promotes host defense or inflammatory pathology remain incompletely understood. Here, we dissect the interplay between IFN-I and IFN{gamma} in macrophage activation using genetically susceptible B6.Sst1S macrophages. We show that, during tumor necrosis factor (TNF) stimulation, susceptible macrophages enter a persistent pathological activation state (pPAS) characterized by sustained lipid peroxidation and super-induction of IFN-I responses. This pathological state is maintained by autocrine IFN-I signaling. In contrast, IFN{gamma} priming prevents pPAS development by enhancing macrophage resilience to oxidative stress, in part through regulation of iron metabolism and induction of ferritin expression. Computational cell state transition assessment and regulation (cSTAR) analysis identified pathways and small molecules predicted to promote the transition of susceptible macrophages toward an IFN{gamma}-induced, Mtb-resistant state. Consistent with these predictions, the CDK4/6 inhibitor trilaciclib reduced lipid peroxidation by regulating iron metabolism, whereas retinoic acid signaling enhanced GPX4 expression and lipid biosynthesis programs. Combined CDK4/6 inhibition and retinoic acid receptor activation efficiently prevented the pathological activation state. Together, these findings delineate a mechanism of IFN-I/IFN{gamma} crosstalk during macrophage activation and identify pharmacologic strategies to prevent IFN-I-dominant, lipid peroxidation-driven macrophage pathology.

immunology↗

bioRxiv2026

T cell-Macrophage Interactions Potentially Influence Chemotherapeutic Response in Ovarian Cancer Patients.

Tumor development and progression involve complex cell-cell interactions and dynamic co-evolution between cancer cells, immune cells and stromal cells in the tumour microenvironment, and this may influence therapeutic resistance. A large proportion of this network relies on direct physical interactions between cells, particularly T-cell mediated interactions. Cell-cell communication inference has now become routine in downstream scRNAseq analysis, but this mostly fails to capture physical cell-cell interactions due to tissue dissociation. Doublets occur naturally in scRNA-seq and are usually excluded from analysis. However, they may represent directly interacting cells that remain undissociated during library preparation. In the present study, we uncover the physical interaction landscape of the ovarian tumour microenvironment using the scRNAseq datasets from 13 treatment-naive ovarian cancer patients. Focusing on T-cell-Macrophage (T-Mac) interaction doublet, we reveal the modulatory effect of macrophages on T cells and the potential influence of this interaction on therapeutic response. Our findings show that T-Macs from resistant patients are functionally polarized to the M2 phenotype and engage T cells to induce T-cell exhaustion. Whereas, T-Macs from sensitive patients are predominantly of the M1 polarized phenotype, physically engaging T cells that lack exhaustion signatures. We also demonstrate that T cells and macrophages in T-Mac doublet are interacting primarily for the purpose of antigen presentation, with the enrichment of several ligand-receptor pairs involved in TCR-MHC interactions and immune synapse formations. We partly validated some of these findings from a spatial transcriptomics dataset of ovarian cancer patients from a separate cohort.

bioinformatics↗

bioRxiv2025

Inferring physical cell-cell communication networks from scRNAseq data using univariate linear models.

Cells in tissues interact by direct physical contact or over short and long distances via secreted mediators. Cell-cell communication inference has now become routine in downstream scRNAseq analysis but this mostly fails to capture physical cell-cell interactions due to tissue dissociation. Multiplets (mostly doublets) in scRNAseq may represent undissociated physically attached cells that become sequenced together. Hence, identifying multiplets may serve as a good starting point to harness scRNAseq data for physical cell-cell interaction inference. In this study, we develop a computational method which utilizes univariate linear models (ULM) to identify multiplets in scRNAseq datasets, predict their cellular compositions, and infer physical cell-cell interaction networks. Indeed, our method showed good sensitivity ([~]56%) with excellent precision ([~]99%) in predicting FACS sorted doublet cell pairs with known constituents (ground truth), recording comparable or superior performance over two other existing methods. Also, applying it to scRNAseq data of partially dissociated tissues containing real multiplets unraveled physical networks which recapitulated the microanatomical structures of the tested tissues. This further underscores the accuracy in our predictions to capture biologically meaningful interactions. Finally, we tested our method on classical scRNAseq datasets and obtained biologically reasonable results. For example, when tested on classical cancer scRNAseq datasets, we recovered important interactions which followed biologically plausible cell interactions, validated by cell-cell colocalization in matched spatial transcriptomics datasets. This reassured the accuracy of our method in depicting physical interactions only between cells that were truly in close proximity in tissues.

bioinformatics↗

bioRxiv2024

MYCN inhibits TrkC-mediated differentiation in neuroblastoma cells via disruption of the PKA signalling pathway

Neuroblastoma is a complex paediatric cancer with a spectrum of clinical outcomes ranging from spontaneous regression to aggressive metastatic disease. Low-risk patients achieve over 90% survival with no or minimal treatment, while high-risk patients face less than 50% survival despite intensive multimodal therapy. Half of the high-risk cases harbour amplification of the MYCN oncogene. In addition to MYCN status, Trk receptors have also been linked to prognosis. TrkA expression is seen with low-risk cases while TrkB expression often occurs in high-risk MYCN-amplified NB. While TrkA and TrkB are well studied in NB, the role of TrkC in neuroblastoma genesis is not clear. Therefore, this study investigates the interplay between MYCN status and NT-3/TrkC signalling in neuroblastoma. Using a panel of neuroblastoma cell lines with varying MYCN levels, we found that TrkC activation leads to neuronal differentiation of MYCN non-amplified cells, whereas it promotes proliferation of MYCN-amplified cells. Temporal phosphoproteomics revealed differential activation of the PKA pathway, which was crucial for TrkC-mediated differentiation. Manipulating the PKA pathway altered cell fate outcomes, underscoring its role. In MYCN-amplified cells, MYCN knockdown increased PKA and CREB activity, shifting the phenotype towards differentiation. Analysis of neuroblastoma patient data showed lower expression of PKA pathway genes in MYCN-amplified tumours. Additionally, miR-221, upregulated by MYCN, was identified as a suppressor of the PKA/CREB pathway. These findings highlight the context-dependent nature of NT-3/TrkC signalling influenced by MYCN; and suggest therapeutic potential in targeting the PKA pathway to induce differentiation of high-risk MYCN-amplified neuroblastoma.

cancer biology↗

bioRxiv2024

Physical cell-cell interactions regulate transcriptional programmes that control the responses of high grade serous ovarian cancer patients to therapy.

The tumour microenvironment is composed of a complex cellular network involving cancer, stromal and immune cells in dynamic interactions. A large proportion of this network relies on direct physical interactions between cells, which may impact patient responses to clinical therapy. Doublets in scRNA-seq are usually excluded from analysis. However, they may represent directly interacting cells. To decipher the physical interaction landscape in relation to clinical prognosis, we inferred a physical cell-cell interaction (PCI) network from biological doublets in a scRNA-seq dataset of approximately 18,000 cells, obtained from 7 treatment-naive ovarian cancer patients. Focusing on cancer-stromal PCIs, we uncovered molecular interaction networks and transcriptional landscapes that stratified patients in respect to their clinical responses to standard therapy. Good responders featured PCIs involving immune cells interacting with other cell types including cancer cells. Poor responders lacked immune cell interactions, but showed a high enrichment of cancer-stromal PCIs. To explore the molecular differences between cancer-stromal PCIs between responders and non-responders, we identified correlating gene signatures. We constructed ligand-receptor interaction networks and identified associated downstream pathways. The reconstruction of gene regulatory networks and trajectory analysis revealed distinct transcription factor (TF) clusters and gene modules that separated doublet cells by clinical outcomes. Our results indicate (i) that transcriptional changes resulting from PCIs predict the response of ovarian cancer patients to standard therapy, (ii) that immune reactivity of the host against the tumour enhances the efficacy of therapy, and (iii) that cancer-stromal cell interaction can have a dual effect either supporting or inhibiting therapy responses.

bioinformatics↗

bioRxiv2024

Spatial proteomics and transcriptomics of placenta accreta spectrum

In severe Placenta Accreta Spectrum (PAS), trophoblasts gain deep access in the myometrium (placenta increta). This study investigated alterations at the fetal-maternal interface in PAS cases using a systems biology approach consisting of immunohistochemistry, spatial transcriptomics and proteomics. We identified spatial variation in the distribution of CD4+, CD3+ and CD8+ T-cells at the maternal-interface in placenta increta cases. Spatial transcriptomics identified transcription factors involved in promotion of trophoblast invasion such as AP-1 subunits ATF-3 and JUN, and NFKB were upregulated in regions with deep myometrial invasion. Pathway analysis of differentially expressed genes demonstrated that degradation of extracellular matrix (ECM) and class 1 MHC protein were increased in increta regions, suggesting local tissue injury and immune suppression. Spatial proteomics demonstrated that increta regions were characterised by excessive trophoblastic proliferation in an immunosuppressive environment. Expression of inhibitors of apoptosis such as BCL-2 and fibronectin were increased, while CTLA-4 was decreased and increased expression of PD-L1, PD-L2 and CD14 macrophages. Additionally, CD44, which is a ligand of fibronectin that promotes trophoblast invasion and cell adhesion was also increased in increta regions. We subsequently examined ligand receptor interactions enriched in increta regions, with interactions with ITG{beta}1, including with fibronectin and ADAMS, emerging as central in increta. These ITG{beta}1 ligand interactions are involved in activation of epithelial-mesenchymal transition and remodelling of ECM suggesting a more invasive trophoblast phenotype. In PAS, we suggest this is driven by fibronectin via AP-1 signalling, likely as a secondary response to myometrial scarring. Overall, this study suggests the biological processes leading to deep trophoblast invasion in the myometrium in placenta increta are as a result of upregulation of transcription factors and subsequent genes and proteins which promote trophoblast invasion. This occurs in a locally immune suppressed environment, with increased ECM degradation suggesting these findings are secondary to iatrogenic uterine injury. Significance statementPlacenta Accreta Spectrum (PAS) is a rare pregnancy complication, where the placenta fails to separate from the womb resulting in severe bleeding, which is associated with significant maternal morbidity and mortality. As Caesarean section rates increase, the incidence of PAS is increasing. The underlying pathophysiology of PAS is poorly understood. Here, we apply a spatial multi-omic approach to explore the biologic changes at the maternal-fetal interface in severe PAS (placenta increta). Using spatial transcriptomics and proteomics, we identified genes and proteins that are dysregulated in severe PAS involving processes such as extracellular matrix degradation, local immune suppression and promotion of epithelial-mesenchymal transition. This study provides new insights into the biological changes and underlying pathophysiology leading to placenta increta.

bioinformatics↗

bioRxiv2024

Myc Dysregulation in Activated Macrophages Initiates Iron-Mediated Lipid Peroxidation that Fuels Type I Interferon and Compromises TB Resistance

A quarter of human population is infected with Mycobacterium tuberculosis, but less than 10% of those infected develop pulmonary TB. We developed a genetically defined sst1-susceptible mouse model that uniquely reproduces a defining feature of human TB: the development of necrotic lung granulomas and determined that the sst1-susceptible phenotype was driven by the aberrant macrophage activation. This study demonstrates that the aberrant response of the sst1-susceptible macrophages to prolonged stimulation with TNF is primarily driven by conflicting Myc and antioxidant response pathways leading to a coordinated failure 1) to properly sequester intracellular iron and 2) to activate ferroptosis inhibitor enzymes. Consequently, iron-mediated lipid peroxidation fueled Ifn{beta} superinduction and sustained the Type I Interferon (IFN-I) pathway hyperactivity that locked the sst1-susceptible macrophages in a state of unresolving stress and compromised their resistance to Mtb. The accumulation of the aberrantly activated, stressed, macrophages within granuloma microenvironment led to the local failure of anti-tuberculosis immunity and tissue necrosis. The upregulation of Myc pathway in peripheral blood cells of human TB patients was significantly associated with poor outcomes of TB treatment. Thus, Myc dysregulation in activated macrophages results in an aberrant macrophage activation and represents a novel target for host-directed TB therapies.

immunology↗

bioRxiv2022

Small gene networks can delineate immune cell states and characterize immunotherapy response in melanoma

BackgroundSingle-cell sequencing studies have elucidated some of the underlying mechanisms responsible for immune checkpoint inhibitor (ICI) response, but are difficult to implement as a general strategy or in a clinical diagnostic setting. In contrast, bulk RNAseq is now routine for both research and clinical applications. Therefore, our analysis extracts small transcription factor-directed co-expression networks (regulons) from single-cell RNA-seq data and uses them to deconvolute immune functional states from bulk RNA-seq data to characterize patient responses. MethodsRegulons were inferred in pre-treatment CD45+ cells from metastatic melanoma samples (n=19) treated with first-line ICI therapy (discovery dataset). A logistic regression-based classifier identified immune cell states associated with response, which were characterized according to differentially active, cell-state specific regulons. The complexity of these regulons was reduced and scored in bulk RNAseq melanoma samples from four independent studies (n=209, validation dataset). Patients were clustered according to their regulon scores, and the associations between cluster assignment, response, and survival were determined. Intercellular communication analysis of cell states was performed, and the resulting effector genes were analyzed by trajectory inference. ResultsRegulons preserved the information of gene expression data and accurately delineated immune cell phenotypes, despite reducing dimensionality by > 100-fold. Four cell states, termed exhausted T cells, monocyte lineage cells, memory T cells, and B cells, were associated with therapeutic responses in the discovery dataset. The cell states were characterized by seven differentially active and specific regulons that showed low specificity in non-immune cells. Four clusters with significantly different response outcomes (P <0.001) were identified in the bulk RNAseq validation cohort. An intercellular link between exhausted T cells and monocyte lineage cells was established, whereby their cell numbers were correlated, and exhausted T cells predicted prognosis as a function of monocyte lineage cell number. Analysis of ligand - receptor expression suggested that monocyte lineage cells drive exhausted T cells into terminal exhaustion through programs that regulate antigen presentation, chronic inflammation, and negative co-stimulation. ConclusionsRegulon-based characterization of cell states provides robust and functionally informative markers that can deconvolve bulk RNA-seq data to identify ICI responders.

immunology↗

bioRxiv2020

Maladaptive oxidative stress cascade drives type I interferon hyperactivity in TNF activated macrophages promoting necrosis in murine tuberculosis granulomas

Tuberculosis remains a critical infectious disease world-wide. The development of novel therapeutic strategies requires greater understanding of host factors that contribute to disease susceptibility. A major unknown in TB pathogenesis is the mechanism of necrosis in TB granulomas that leads to the massive lung tissue damage and cavity formation necessary for the pathogen transmission. In humans, TB progression has been linked to hyperactivity of type I IFN (IFN-I) pathway, the primary cause of which remains elusive. We studied the mechanistic drivers of pulmonary TB progression using a unique model B6J.C3-Sst1C3HeB/Fej Krmn mice that develop human-like necrotic TB granulomas and IFN-I hyperactivity. We established that IFN{beta} super-induction occurred in the susceptible macrophages in response to continuous TNF stimulation in the context of a dysregulated antioxidant defense. We observed that unresolving oxidative stress amplified the induction of IFN{beta} through JNK activation and induced the Integrated Stress Response via PKR activation as a compensatory pathway. Subsequently, PKR amplifies IFN{beta} upregulation, forming a positive feedback loop, maintaining the hyperinflammatory state in susceptible macrophages and leading to mitochondrial dysfunction. Thus, within the inflammatory milieu, a cell-intrinsic mechanism of chronic regulatory dysfunction and unresolved stress gradually weakens the macrophage and ultimately promotes the necrotization of TB granulomas. The aberrant macrophage response to TNF can be prevented by an iron chelator and inhibitor of lipid peroxidation, ferrostatin-1. Moreover, ferrostatin treatment increased macrophage survival and boosted bacterial control in the TNF-stimulated macrophages infected with virulent Mtb. These findings identify targets for host-directed therapeutics to interrupt necrotization in TB granulomas.

immunology↗

bioRxiv2020

Characterisation of the Renal Cortical Transcriptome Following Roux-en-Y Gastric Bypass Surgery in Experimental Diabetic Kidney Disease.

IntroductionRoux-en-Y Gastric Bypass Surgery (RYGB) reduces albuminuria and the long-term incidence of end-stage renal disease in patients with obesity and diabetes. Preclinical modelling in experimental diabetic kidney disease (DKD) demonstrates that improvements in glomerular structure likely underpin these findings. Research Design & MethodsIn adult male Zucker Diabetic Fatty (ZDF) rats, we profiled the effect of RYGB on weight and metabolic control as well biochemical, structural and ultrastructural indices of diabetic renal injury. Furthermore, we sequenced the renal cortical transcriptome in these rats and used bioinformatic pathway analyses to characterise the transcriptional alterations governing the renal reparative response to RYGB ResultsIn parallel with improvements in weight and metabolic control, RYGB reduced albuminuria, glomerulomegaly, podocyte stress, and podocyte foot process effacement. Pathway analysis of RYGB-induced transcriptomic changes in the renal cortex highlighted correction of disease-associated alterations in fibrosis, inflammation and biological oxidation pathways. RYGB reversed disease-associated changes in the expression of TGF-{beta} superfamily genes that strongly correlated with improvements in structural measures of glomerulopathy. ConclusionsImproved glomerular structure in ZDF rats following RYGB is underpinned by pathway level changes, including interruption of the TGF-{beta} driven pro-fibrotic programme. Our data provide an important layer of experimental support for clinical evidence demonstrating that RYGB arrests renal damage in patients with obesity and Type 2 Diabetes. KEY MESSAGESO_LIWhat is already known about this subject? O_LIRYGB is an effective treatment for obesity and type 2 diabetes and longitudinal cohort studies have demonstrated its albuminuria lowering effect and evidence of longer term reno-protection. C_LIO_LIStudies in pre-clinical models of diabetic kidney disease have described favourable changes in measures of renal structure and ultrastructure following RYGB. C_LI C_LIO_LIWhat are the new findings? O_LIThe present study directly correlates structural and ultrastructural improvements in the ZDF rat kidney following RYGB with corrective shifts in the global renal transcriptome. C_LIO_LIChronic renal remodelling responses in experimental DKD that are governed by TGF-{beta} signalling are interrupted and reversed by RYGB. C_LI C_LIO_LIHow might these results change the focus of research or clinical practice? O_LIThese data will support further interrogation of RYGB specific shifts in the renal transcriptome with a view to identifying tractable targets for treatment response biomarkers and bariatric mimetic based diet and pharmacotherapy based interventions. C_LI C_LI

molecular biology↗

bioRxiv2020

Towards predictive nanotoxicology: from roundabout of molecular events to chronic inflammation prediction

Nanomaterial-induced diseases cannot be reliably predicted because of the lack of clearly identified causal relationships, in particular between acute exposures and chronic symptoms. By applying advanced microscopies and omics to in vitro and in vivo systems, together with in silico molecular modelling, we have here determined that the long-lasting response to a single exposure originates in the counteracting of a newly discovered nanomaterial quarantining and nanomaterial cycling among different lung cell types. This allows us to predict the nanomaterial-induced spectrum of lung inflammation using only in vitro measurements and in silico modelling. Besides its profound implications for cost-efficient animal-free predictive toxicology, our work also paves the way to a better mechanistic understanding of nanomaterial- induced cancer, fibrosis, and other chronic diseases.

molecular biology↗

bioRxiv2018

Transcriptional regulatory mechanisms of fibrosis development in mouse lung tissue exposed to carbon nanotubes

BackgroundCarbon nanotubes (CNTs) usage has rapidly increased in the last few decades due to their unique properties, exploited in various industrial and commercial products. Certain types of CNTs cause adverse health effects, including chronic inflammation and fibrosis. Despite the large number of in vitro and in vivo studies evaluating these effects, many important questions remain unanswered due to a lack of mechanistic understanding of how CNTs induce cellular stress responses. In order to predict CNT toxicity, it is important to understand which transcriptional programs are specifically activated in response to CNTs, and what similarities and differences exist in relation to other toxic inducers exerting similar adverse effects.\n\nResultsA systems biology approach was applied to reveal complex interactions at the molecular level in mouse lung tissue in response to different fibrosis inducers: two types of multi-walled CNTs, NM-401 and NRCWE-26, and bleomycin (BLM). Based on mRNA gene expression profiles, we inferred gene regulatory networks (GRNs) to capture functional hierarchical regulatory structures between genes and their regulators. We found that activities of the transcription factors (TFs) Myc, Arid5a and Mxd1 were associated with the regulation of cytokine transcription in response to CNTs, while in response to BLM treatment, Myc was associated with p53 signaling. TF Litaf was identified as the essential regulator for noncanonical signaling of TLR2/4 driven by CNTs. Despite the different nature of the lung injury caused by CNTs and BLM, we identified common stress response modules, that included DNA damage (TFs: E2f8, E2f1, Foxm1), M1/M2 macrophage polarization (TF: Mafb), Interferon response (TFs: Irf7, Stat2 and Irf9) for all agents.\n\nConclusionsThese results suggest that the reconstruction and analysis of TF-centric gene interaction networks can reveal key targets and regulators of cellular stress responses to toxic agents.

pharmacology and toxicology↗