Biology subjects

Kulkarni, K.

Publications and source records attributed to Kulkarni, K..

9 recordsLinked to original sources

bioRxiv2026

Combinatorial transcription factor interactions drive modular gene regulatory networks

Transcription factors (TFs) cooperatively drive gene regulatory networks (GRNs) to establish transcriptional states. Forced induction of TFs in combination can reprogram cell state by supplanting existing GRNs. Thus, TFs and GRNs are the building blocks to engineering transcriptional state. However, one key challenge is that the relationship between TF combinations and GRNs remains largely uncharacterized and difficult to accurately predict. Here, we apply single-cell overexpression screens to map the combinatorial activities of [~]100 TFs to gene expression states. Our analysis identifies diverse TF combinations driving cell-type specific regulatory programs. Notably, different TF combinations induce shared gene sets with cell-type specific functions, suggesting a modular regulatory architecture of the transcriptome. Furthermore, we define pairwise TF interactions and show that cooperative interactions improve transcriptional reprogramming. Finally, we developed tools to predict combinatorial TF phenotypes. These findings improve our understanding of cell state and how to manipulate it for biomedical applications. HIGHLIGHTSO_LICombinatorial over-expression screens for [~]100 transcription factors (TFs). C_LIO_LIDiverse TF combinations drive cell-type specific regulatory programs. C_LIO_LITF regulatory networks reveal a modular regulatory architecture of the transcriptome. C_LIO_LITF-TF interactions and predictive models enhance reprogramming cocktails. C_LI

genomics↗

bioRxiv2026

Epithelial sensing of vitamin A shapes intestinal antimicrobial defense

Vitamin A is a central regulator of intestinal adaptive immunity, but its role in innate immunity is less defined. Antimicrobial proteins form a chemical barrier that protects the intestinal epithelium from microbial invasion. Among these, REG3 family lectins are induced by the microbiota, yet how nutritional cues intersect with microbial signals to control their expression remains unclear. Here, we show that dietary vitamin A promotes expression of REG3 antimicrobial lectins, including REG3G, in intestinal epithelial cells from both mice and humans. This induction is mediated by retinoic acid and requires retinoic acid receptor (RAR) signaling. Mechanistically, RARs bind directly to the Reg3g promoter adjacent to a STAT3 binding site. As STAT3 mediates microbiota-induced IL-22 signaling in epithelial cells, this arrangement provides a molecular framework for integrating nutritional and microbial inputs at the level of REG3G transcription. Extending these findings, we demonstrate that vitamin A-retinoic acid signaling similarly promotes expression of -defensin antimicrobial proteins. Together, these findings define a transcriptional mechanism by which vitamin A enhances epithelial antimicrobial defenses and strengthens mucosal innate immunity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/710399v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@18dd8aforg.highwire.dtl.DTLVardef@18cf2fdorg.highwire.dtl.DTLVardef@a4dc89org.highwire.dtl.DTLVardef@18aa9c7_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIVitamin A promotes epithelial expression of REG3 antimicrobial proteins in the intestine C_LIO_LIRetinoic acid receptors (RARs) directly activate mouse Reg3g and human REG3G transcription C_LIO_LIRARs bind the Reg3g promoter adjacent to STAT3, integrating nutritional and microbial signals C_LIO_LIVitamin A-RAR signaling broadly regulates epithelial antimicrobial programs, including -defensins C_LI

immunology↗

bioRxiv2025

Bacterial ubiquitin ligase engineered for small molecule and protein target identification

The Legionella SidE effectors ubiquitinate host proteins independently of the canonical E1-E2 cascade. Here we engineer the SidE ligases to develop a modular proximity ligation approach for the identification of targets of small molecules and proteins, which we call SidBait. We validate the method with known small molecule-protein interactions and use it to identify CaMKII as an off-target interactor of the breast cancer drug ribociclib. Structural analysis and activity assays confirm that ribociclib binds the CaMKII active site and inhibits its activity. We further customize SidBait to identify protein-protein interactions, including substrates for enzymes, and discover the F-actin capping protein (CapZ) as a target of the Legionella effector RavB during infection. Structural and biochemical studies indicate that RavB allosterically binds CapZ and decaps actin, thus functionally mimicking eukaryotic CapZ interacting proteins. Collectively, our results establish SidBait as a reliable tool for identifying targets of small molecules and proteins.

molecular biology↗

bioRxiv2024

Efficacy of dynamic eigenvalue in anticipating and distinguishing tipping points

The presence of tipping points in several natural systems necessitates having improved early warning indicators to provide accurate signals of an impending transition to a contrasting state while also detecting the type of transition. Various early warning signals (EWSs) have been devised to forecast the occurrence of tipping points, also called critical transitions. Dynamic eigenvalue (DEV) is a recently proposed EWS that can not only predict the occurrence of a transition but also certain types of accompanying bifurcations. Here, we study the effectiveness and limitations of DEV as an EWS for diverse kinds of critical phenomena. We demonstrate that DEV is a powerful EWS that shows promising results in anticipating catastrophic (first-order or discontinuous) and non-catastrophic (second-order or continuous) transitions in discrete and continuous dynamical systems. However, it falls short in the case of piecewise smooth systems. Further, the ability of DEV to forecast the type of transition is limited, as it cannot differentiate saddle-node bifurcation from transcritical and pitchfork bifurcations. Despite these limitations, we show that DEV can work as a robust indicator for varying rates at which the transition is approached and with systems involving colored noise.

ecology↗

bioRxiv2020

Wavelet coherence phases decode the universal switching mechanism of Ras GTPase superfamily

Ras superfamily GTPases are molecular switches which regulate critical cellular processes. Extensive structural and computational studies on these G proteins have established a general framework for their switching mechanism, which involves conformational changes in their two loops, Switch I and Switch II, upon GTP binding and hydrolysis. Since the extent of these conformational changes is not uniform amongst the members of the Ras superfamily, there is no generic modus operandi defining their switching mechanism. Here, we have developed a novel approach employing wavelet coherence analysis to correlate the structural changes with their functional states. Our analysis shows that the structural coupling between the Switch I and Switch II regions is manifested in terms of conserved wavelet coherence phases, which could serve as useful parameters to define functional states of the GTPases. In oncogenic GTPases mutants, this phase coupling gets disentangled, which perhaps provides an alternative explanation for their aberrant function. We have tested the statistical significance of the observed phase angle correlations on multiple switch region conformers, generated through MD simulations.

biophysics↗

bioRxiv2020

Controlling the Growth of the Skin Commensal Staphylococcus epidermidis Using D-Alanine Auxotrophy

Using live microbes as therapeutic candidates is a strategy that has gained traction across multiple therapeutic areas. In the skin, commensal microorganisms play a crucial role in maintaining skin barrier function, homeostasis, and cutaneous immunity. Alterations of the homeostatic skin microbiome are associated with a number of skin diseases. Here, we present the design of an engineered commensal organism, Staphylococcus epidermidis, for use as a live biotherapeutic product (LBP) candidate for skin diseases. The development of novel bacterial strains whose growth can be controlled without the use of antibiotics, or genetic elements conferring antibiotic resistance, enables modulation of therapeutic exposure and improves safety. We therefore constructed an auxotrophic strain of S. epidermidis that requires exogenously supplied D-alanine. The S. epidermidis strain, NRRL B-4268 {Delta}alr1{Delta}alr2{Delta}dat (SE{Delta}{Delta}{Delta}) contains deletions of three biosynthetic genes: two alanine racemase genes, alr1 and alr2 (SE1674 and SE1079), and the D-alanine aminotransferase gene, dat (SE1423). These three deletions restricted growth in D-alanine deficient media, pooled human blood, and skin. In the presence of D-alanine, SE{Delta}{Delta}{Delta} colonized and increased expression of human {beta}-defensin 2 in cultured human skin models in vitro. SE{Delta}{Delta}{Delta}, showed a low propensity to revert to D-alanine prototrophy, and did not form biofilms on plastic in vitro. These studies support the potential safety and utility of SE{Delta}{Delta}{Delta} as a live biotherapeutic strain whose growth can be controlled by D-alanine.

microbiology↗

bioRxiv2019

De novo transcriptome profiling of mustard aphid (Lipaphis erysimi) and differential expression of transcripts associated with developmental stages, feeding and non-feeding conditions

Lipaphis erysimi is a Brassicaceae specialist aphid, which causes significant losses in yield and/or reduction of oil content of vegetable and oilseed brassicas and is a major pest in the Indian subcontinent. This study reports the de novo transcriptome of L. erysimi for the first time. We also present a comparative analysis of nymphs and adult transcriptomes to study the differential expression profiles associated with different developmental stages as well as different feeding conditions. For this, RNA-seq was performed on three different biological samples adults, nymphs (with all nymph stages pooled) and adults starved for 3 hours (referred to as Adult Feeding, AF; Nymphs Feeding, NF, and Adult Starved_3 hr, ANF samples henceforth). A final transcriptome comprising 52,652 transcripts of 1064bp average length and N50 value of 1806 bp was generated. A total of 27,112 transcripts were annotated with insect proteins from SwissProt, of which 4128 transcripts were components of 165 KEGG pathways. A total of 17,296 transcripts were classified based on their Gene Ontology. Potential transcripts for host selection, detoxification, salivary proteins and effectors, molecular chaperones and developmental genes were identified. A total of 23,532 transcripts that remained unannotated were subjected to BLAST against aphid sequences available at AphidBase and a total of 3091 transcripts had hits with sequences of other aphids in the database, out of which 1380 had protein hits. A total of 20441 found to share no homology to any sequence available in the public domain and could therefore represent novel aphid genes or sequences that are unique to L. erysimi. This is an exploratory study with no biological replicates. However, the significant repertoire of feeding- and development-related genes and their differential expression profiles generated in this study adds to the limited data available on L. erysimi and it would facilitate studies on the molecular basis of aphid feeding and development. This could also allow identification of novel target genes for development of RNAi-based aphid control methods.

systems biology↗

bioRxiv2018

A whole-brain and cross-diagnostic perspective on functional brain network dysfunction

A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations have seemed to support various theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in broad, whole-brain perspective. Using a graph distance measure - connectome-wide correlation - we found that whole-brain resting-state functional network organization in humans is highly similar across a variety of mental diseases and healthy controls. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease those differences are informative. Such small network alterations may reflect the fact that most psychiatric patients maintain overall cognitive abilities similar to those of healthy individuals (relative to, e.g., the most severe schizophrenia cases), such that whole-brain functional network organization is expected to differ only subtly even for mental diseases with devastating effects on everyday life. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases.

neuroscience↗

bioRxiv2017

Mapping the human brain’s cortical-subcortical functional network organization

Highlights O_LILarge-scale functional network map of the entire human brain\nC_LIO_LICortical networks based on multiband fMRI, recently-identified regions\nC_LIO_LISubcortical extension of networks covering all subcortical structures\nC_LIO_LIMultiple quality assessments demonstrate robustness of functional networks\nC_LIO_LINetwork atlas released as public resource, providing framework for future studies\nC_LI\n\nABSTRACTUnderstanding complex systems such as the human brain requires characterization of the systems architecture across multiple levels of organization - from neurons, to local circuits, to brain regions, and ultimately large-scale brain networks. Here we focus on characterizing the human brains large-scale network organization, as it provides an overall framework for the organization of all other levels. We developed a highly principled approach to identify cortical network communities at the level of functional systems, calibrating our community detection algorithm using extremely well-established sensory and motor systems as guides. Building on previous network partitions, we replicated and expanded upon well-known and recently identified networks, including several higher-order cognitive networks such as a left-lateralized language network. We expanded these cortical networks to subcortex, revealing 358 highly organized subcortical parcels that take part in forming whole-brain functional networks. Notably, the identified subcortical parcels are similar in number to a recent estimate of the number of cortical parcels (360). This whole-brain network atlas - released as an open resource for the neuroscience community - places all brain structures across both cortex and subcortex into a single large-scale functional framework, with the potential to facilitate a variety of studies investigating large-scale functional networks in health and disease.

neuroscience↗