Biology subjects

Sarker, B.

Publications and source records attributed to Sarker, B..

6 recordsLinked to original sources

bioRxiv2023

Identifying LasR quorum sensors with improved signal specificity by mapping the sequence-function landscape

Programmable intercellular signaling using components of naturally-occurring quorum sensing can allow for coordinated functions to be engineered in microbial consortia. LuxR-type transcriptional regulators are widely used for this purpose and are activated by homoserine lactone (HSL) signals. However, they often suffer from imperfect molecular discrimination of structurally similar HSLs, causing misregulation within engineered consortia containing multiple HSL signals. Here, we studied one such example, the regulator LasR from Pseudomonas aeruginosa. We elucidated its sequence-function relationship for ligand specificity using targeted protein engineering and multiplexed high-throughput biosensor screening. A pooled combinatorial saturation mutagenesis library (9,486 LasR DNA sequences) was created by mutating six residues in LasRs {beta}5 sheet with single, double, or triple amino acid substitutions. Sort-seq assays were performed in parallel using cognate and non-cognate HSLs to quantify each corresponding sensors response to each HSL signal, which identified hundreds of highly specific variants. Sensor variants identified were individually assayed and exhibited up to 60.6-fold (p = 0.0013) improved relative activation by the cognate signal compared to the wildtype. Interestingly, we uncovered prevalent mutational epistasis and previously unidentified residues contributing to signal specificity. The resulting sensors with negligible signal crosstalk could be broadly applied to engineer bacteria consortia.

synthetic biology↗

bioRxiv2023

Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis using LuxR-type Regulators

A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that gram-negative and gram-positive bacteria generally communicate via homoserine lactones (HSL) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors ([≥] 20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.

synthetic biology↗

bioRxiv2023

Components of Isolated Skeletal Muscle Differentiated Through Antibody Validation

Isolation of skeletal muscles allows for the exploration of many complex diseases. Fibroblasts and myoblast play important roles in skeletal muscle morphology and function. However, skeletal muscles are complex and made up of many cellular populations and validation of these populations is highly important. Therefore, in this article, we discuss a comprehensive method to isolate mice skeletal muscle, create satellite cells for tissue culture, and use immunofluorescence to validate our approach. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/541600v2_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@165b34dorg.highwire.dtl.DTLVardef@1de9976org.highwire.dtl.DTLVardef@12d3cfeorg.highwire.dtl.DTLVardef@ff660c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

MetaLLM: Residue-wise Metal ion Prediction UsingDeep Transformer Model

Proteins bind to metals such as copper, zinc, magnesium, etc., serving various purposes such as importing, exporting, or transporting metal in other parts of the cell as ligands and maintaining stable protein structure to function properly. A metal binding site indicates the single amino acid position where a protein binds a metal ion. Manually identifying metal binding sites is expensive, laborious, and time-consuming. A tiny fraction of the millions of proteins in UniProtKB - the most comprehensive protein database - are annotated with metal binding sites, leaving many millions of proteins waiting for metal binding site annotation. Developing a computational pipeline is thus essential to keep pace with the growing number of proteins. A significant shortcoming of the existing computational methods is the consideration of the long-term dependency of the residues. Other weaknesses include low accuracy, absence of positional information, hand-engineered features, and a pre-determined set of residues and metal ions. In this paper, we propose MetaLLM, a metal binding site prediction technique, by leveraging the recent progress in self-supervised attention-based (e.g. Transformer) large language models (LLMs) and a considerable amount of protein sequences publicly available. LLMs are capable of modelling long residual dependency in a sequence. The proposed MetaLLM uses a transformer pre-trained on an extensive database of protein sequences and later fine-tuned on metal-binding proteins for multi-label metal ions prediction. A 10-fold cross-validation shows more than 90% precision for the most prevalent metal ions.

bioinformatics↗

bioRxiv2022

A fast yet force-effective mode of collective cell migration on aligned fibers due to rapid stabilization of contractile forces

Cell collectives, like other motile entities, generate and use forces to move forward. Here, we ask whether environmental configurations alter this proportional force-speed relationship, since aligned extracellular matrix fibers are known to cause directed migration. We show that aligned fibers serve as active conduits for spatial propagation of cellular mechanotransduction through matrix exoskeleton, leading to efficient directed collective cell migration. Epithelial (MCF10A) cell clusters adhered to soft substrates with aligned collagen fibers (AF) migrate faster with much lesser traction forces, compared to random fibers (RF). Fiber alignment causes higher motility waves and transmission of normal stresses deeper into cell monolayer while minimizing shear stresses and increased cell-division based fluidization. By contrast, fiber randomization induces cellular jamming due to breakage in motility waves, disrupted transmission of normal stresses, and heightened shear driven flow. Using a novel motor-clutch model, we explain that such force-effective fast migration phenotype occurs due to rapid stabilization of contractile forces at the migrating front, enabled by higher frictional forces arising from simultaneous compressive loading of parallel fiber-substrate connections. We also model haptotaxis to show that increasing ligand connectivity (but not continuity) increases migration efficiency. According to our model, increased rate of front stabilization via higher resistance to substrate deformation is sufficient to capture durotaxis. Thus, our findings reveal a new paradigm wherein the rate of leading-edge stabilization determines the efficiency of supracellular collective cell migration.

biophysics↗

bioRxiv2022

Mechanically primed cells transfer memory to fibrous matrices for persistent invasion

In disease and development, cells sense and migrate across mechanically dissimilar environments. We investigated whether mechanical memory of past environments empowers cells to navigate new, three-dimensional environments. Here, we show that cells primed by stiff matrices apply higher forces, compared to soft-primed cells, to accumulate and align collagen fibers towards sustained invasion. This priming advantage persists in dense or stiffened collagen. Through an energy-minimization model, we elucidate how memory-laden cells overcome mechanosensing of softer or challenging environments via a cell-matrix transfer of memory. Consistent with model predictions, depletion of -catenin and YAP hamper coordinated forces and cellular memory required for collagen remodeling before invasion. We release tension in collagen fibers via laser ablation and disable fiber remodeling by lysyl-oxidase inhibition; both of which disrupt cell-to-matrix transfer of memory and reduce invasion. These results have implications for cancer, fibrosis, and aging, where potential matrix memory may generate prolonged cellular response. One-Sentence SummaryCell invasion across mechanically dissimilar environments is mediated by force-based storage and extraction of cell and matrix memory.

biophysics↗