Biology subjects

Dhar, J.

Publications and source records attributed to Dhar, J..

4 recordsLinked to original sources

bioRxiv2023

Synergistic phenotypic shifts during domestication promote plankton-to-biofilm transition in purple sulfur bacterium Chromatium okenii

The ability to isolate microorganisms from natural environments to pure cultures under optimized laboratory settings has markedly improved our understanding of microbial ecology. Laboratory-induced artificial growth conditions often diverge from those in natural ecosystems, forcing wild isolates into selective pressures which are distinct compared to those in nature. Consequently, fresh isolates undergo diverse eco-physiological adaptations mediated by modification of key phenotypic traits. For motile microorganisms, we still lack a biophysical understanding of the relevant traits which emerge during domestication, and possible mechanistic interrelations between them which could ultimately drive short-to-long term microbial adaptation under laboratory conditions. Here, using microfluidics, atomic force microscopy (AFM), quantitative imaging, and mathematical modelling, we study phenotypic adaptation of natural isolates of Chromatium okenii, a motile phototrophic purple sulfur bacterium (PSB) common to meromictic settings, grown under ecologically-relevant laboratory conditions over multiple generations. Our results indicate that the naturally planktonic C. okenii populations leverage synergistic shifts in cell-surface adhesive interactions, together with changes in their cell morphology, mass density, and distribution of intracellular sulfur globules, to supress their swimming traits, ultimately switching to a sessile lifeform under laboratory conditions. A computational model of cell mechanics confirms the role of the synergistic phenotypic shifts in suppressing the planktonic lifeform. Over longer domestication periods ([~]10 generations), the switch from planktonic to sessile lifeform is driven by loss of flagella and enhanced adhesion. By investigating key phenotypic traits across different physiological stages of lab-grown C. okenii, we uncover a progressive loss of motility via synergistic phenotypic shifts during the early stages of domestication, which is followed by concomitant deflagellation and enhanced surface attachment that ultimately drive the transition of motile sulphur bacteria to a sessile biofilm state. Our results establish a mechanistic link between suppression of motility and surface attachment via synergistic phenotypic changes, underscoring the emergence of adaptive fitness under felicitous laboratory conditions that comes at a cost of lost ecophysiological traits tailored for natural environments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/563228v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@fcb6b0org.highwire.dtl.DTLVardef@13e18d0org.highwire.dtl.DTLVardef@1cf3ee6org.highwire.dtl.DTLVardef@12a837b_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Phytoplankton tune local pH to actively modulate circadian swimming behavior

Diel vertical migration (DVM), the diurnal exodus of motile phytoplankton between the light- and nutrient-rich aquatic regions, is governed by endogenous biological clocks. Many species exhibit irregular DVM patterns wherein out-of-phase gravitactic swimming-relative to that expected due to the endogenous rhythm-is observed. How cells achieve and control this irregular swimming behavior, and its impact on biological fitness remain poorly understood. Combining local environmental monitoring with behavioral and physiological analyses of motile bloom-forming Heterosigma akashiwo cells, we report that phytoplankton species modulate their DVM pattern by progressively tuning local pH, yielding physiologically equivalent yet behaviorally distinct gravitactic sub-populations which remain separated vertically within a visibly homogeneous cell distribution. Individual and population-scale tracking of the isolated top and bottom sub-populations revealed similar gravitactic (swimming speed and stability) and physiological traits (growth rate and maximum photosynthetic yield), suggesting that the sub-populations emerge due to mutual co-existence. Exposing the top (bottom) sub-population to the spent media of the bottom (top) counterpart recreates the emergent vertical distribution, while no such phenomenon was observed when the sub-populations were exposed to their own spent media. A model of swimming mechanics based on the quantitative analysis of cell morphologies confirms that the emergent sub-populations represent distinct swimming stabilities, resulting from morphological transformations after the cells are exposed to the spent media. Together with the corresponding night-time dataset, we present an integrated picture of the circadian swimming, wherein active chemo-regulation of the local environment underpins motility variations for potential ecological advantages via intraspecific division of labor over the day-night cycle. This chemo-regulated migratory trait offers mechanistic insights into the irregular diel migration, relevant particularly for modelling phytoplankton transport, fitness and adaptation as globally ocean waters see a persistent drop in the mean pH. One sentence summaryActive regulation of local pH diversifies the diel vertical migration of motile phytoplankton.

biophysics↗

bioRxiv2023

MACI: A machine learning-based approach to identify drug classes of antibiotic resistance genes from metagenomic data

Novel methodologies are now essential for identification of antibiotic resistant pathogens in order to resist them. Here, we are presenting a model, MACI (Machine learning-based Antibiotic resistance gene-specific drug Class Identification) that can take metagenomic fragments as input and predict the drug class of antibiotic resistant genes. We trained the model to learn underlying patterns of genes using the Comprehensive Antibiotic Resistance Database. It comprises of 116 drug classes with a total of 2960 representative sequences. Among these 116 drug classes, we found 22 categories (contributing approximately 85% of the overall sequence-data) surpassed other 94 drug classes based on the number of fragments. The model showed an average precision of 0.83 and a recall of 0.81 for these 22 drug classes. Moreover, the model predicted multidrug resistant classes with higher performance score (precision and recall: 0.9 and 0.88 respectively) compared to single drug resistant categories (0.77 and 0.75). Post to this, we analysed these 22 drug classes to find out class-specific overlapping patterns of nucleotides that led to accurate classification. This way, we found five drug classes viz. "carbapenem;cephalosporin;penam", "cephalosporin", "cephamycin", "cephalosporin;monobactam;penam;penem", and "fluoroquinolone". Additionally, the positions of these significant patterns corroborated with the functional domains of majority of antibiotic resistance genes in that drug class, indicating their biological importance. These class-specific patterns play a pivotal role in rapid identification of some drug classes comprising antibiotic resistance genes. Further analysis showed that bacterial species, containing these five-drug classes, were found to have well-known multidrug resistance property.

bioinformatics↗

bioRxiv2021

Active reconfiguration of cytoplasmic lipid droplets governs migration of nutrient-limited phytoplankton

As open oceans continue to warm, modified currents and enhanced stratification exacerbate nitrogen and phosphorus limitation, constraining primary production. The ability to migrate vertically bestows motile phytoplankton a crucial-albeit energetically expensive-advantage toward vertically redistributing for optimal growth, uptake and resource storage in nutrient-limited water columns. However, this traditional view discounts the possibility that the phytoplankton migration strategy may be actively selected by the storage dynamics when nutrients turn limiting. Here we report that storage and migration in phytoplankton are coupled traits, whereby motile species harness energy storing lipid droplets (LDs) to biomechanically regulate migration in nutrient limited settings. LDs grow and translocate-directionally-within the cytoplasm to accumulate below the cell nucleus, tuning the speed, trajectory and stability of swimming cells. Nutrient reincorporation reverses the LD translocation, restoring the homeostatic migratory traits measured in population-scale millifluidic experiments. Combining intracellular LD tracking and quantitative morphological analysis of red-tide forming alga, Heterosigma akashiwo, along with a model of cell mechanics, we discover that the size and spatial localization of growing LDs govern the ballisticity and orientational stability of migration. The strain-specific shifts in migration which we identify here are amenable to a selective emergence of mixotrophy in nutrient-limited phytoplankton. We rationalize these distinct behavioral acclimatization in an ecological context, relying on concomitant tracking of the photophysiology and reactive oxygen species (ROS) levels, and propose a dissipative energy budget for motile phytoplankton alleviating nutrient limitation. The emergent resource acquisition strategies, enabled by distinct strain-specific migratory acclimatizing mechanisms, highlight the active role of the reconfigurable cytoplasmic LDs in guiding vertical movement. By uncovering the mechanistic coupling between dynamics of intracellular changes to physiologically-governed migration strategies, this work offers a tractable framework to delineate diverse strategies which phytoplankton may harness to maximize fitness and resource pool in nutrient-limited open oceans of the future. One sentence summaryPhytoplankton harness reconfigurable lipid droplets to biomechanically tune migratory strategies in dynamic nutrient landscapes.

biophysics↗