Biology subjects

Jayakumar, P.

Publications and source records attributed to Jayakumar, P..

4 recordsLinked to original sources

bioRxiv2025

Modulating gene expression and protein secretion in the bacterial predator Bdellovibrio bacteriovorus

The predatory bacterium Bdellovibrio bacteriovorus kills and consumes other bacteria, thrives in diverse environments and holds great potential to address major challenges in medicine, agriculture, and biotechnology. As a bacterial predator it represents an alternative to traditional antimicrobial strategies to combat multidrug-resistant bacterial pathogens and prevent food waste, while the multitude of predatory enzymes it produces hold potential for biotechnological applications. However, the limited availability of versatile genetic tools and secretion assays constrain both fundamental studies and bioengineering of B. bacteriovorus. Here, we developed a molecular toolbox for B. bacteriovorus by systematically tuning gene expression and secretion of a reporter protein. We investigated functional native and synthetic promoters from the Anderson library with varying expression levels and demonstrated their efficacy in driving expression of the fluorescent reporter protein mScarletI3 at both the population and single-cell level. Additionally, we evaluated different ribosomal binding sites (RBS) to fine-tune gene expression. To examine secretion, we established a novel protocol to quantify extracellular release of a Nanoluc luciferase reporter protein in B. bacteriovorus using different native Sec-dependent signal sequences. We anticipate that the newly developed genetic toolkit and techniques will advance research on this fundamental predator-prey system, laying the foundation for its broader application and future bioengineering efforts. This work will pave the way for tailored applications of B. bacteriovorus in microbial ecology, agriculture, biotechnology, and medicine.

microbiology↗

bioRxiv2023

The genetic architecture of the human skeletal form

The human skeletal form underlies our ability to walk on two legs, but unlike standing height, the genetic basis of limb lengths and skeletal proportions is less well understood. Here we applied a deep learning model to 31,221 whole body dual-energy X-ray absorptiometry (DXA) images from the UK Biobank (UKB) to extract 23 different image-derived phenotypes (IDPs) that include all long bone lengths as well as hip and shoulder width, which we analyzed while controlling for height. All skeletal proportions are highly heritable ([~]40-50%), and genome-wide association studies (GWAS) of these traits identified 179 independent loci, of which 102 loci were not associated with height. These loci are enriched in genes regulating skeletal development as well as associated with rare human skeletal diseases and abnormal mouse skeletal phenotypes. Genetic correlation and genomic structural equation modeling indicated that limb proportions exhibited strong genetic sharing but were genetically independent of width and torso proportions. Phenotypic and polygenic risk score analyses identified specific associations between osteoarthritis (OA) of the hip and knee, the leading causes of adult disability in the United States, and skeletal proportions of the corresponding regions. We also found genomic evidence of evolutionary change in arm-to-leg and hip-width proportions in humans consistent with striking anatomical changes in these skeletal proportions in the hominin fossil record. In contrast to cardiovascular, auto-immune, metabolic, and other categories of traits, loci associated with these skeletal proportions are significantly enriched in human accelerated regions (HARs), and regulatory elements of genes differentially expressed through development between humans and the great apes. Taken together, our work validates the use of deep learning models on DXA images to identify novel and specific genetic variants affecting the human skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis.

genomics↗

bioRxiv2022

Evolution of the quorum sensing systems in Pseudomonas aeruginosa can involve both loss of regulon function and network modulation

Pseudomonas aeruginosa populations evolving in cystic fibrosis (CF) lungs, animal infection models, natural environments or in vitro undergo extensive genetic adaption and diversification. A common mutational target is the quorum sensing (QS) regulon, a three-unit regulatory system that controls the expression of a suite of virulence factors and secreted public goods. Three scenarios have been advocated to explain selection for QS mutants, which include (I) disuse of the regulon, (II) cheating on public goods, or (III) modulation of the network. Here, we test these scenarios by examining a set of 61 QS mutants from an experimental evolution study. We observed non-synonymous mutations in all three QS systems - Las, Rhl and PQS. Most Las mutants carried large deletions, resulting in loss of QS function, and the inability to produce QS-regulated traits (scenario I or II). Conversely, phenotypic and gene expression analyses of Rhl mutants support network modulation (scenario III), as these mutants overexpressed the Las and Rhl regulators and showed an altered QS-regulated trait production portfolio. PQS mutants also showed patterns of network modulation (scenario III), spurring strain diversification and phenotypic trade-offs, where the upregulation of certain QS traits is associated with the downregulation of others. Overall, our results indicate that mutations in different QS systems lead to diverging effects on the social portfolio of bacterial populations. These mutations might not only affect the plasticity and diversity of evolved populations but could also impact bacterial fitness and virulence in infections. ImportancePseudomonas aeruginosa uses quorum sensing (QS), a three-unit multi-layered network, to coordinate expression of traits for growth and virulence in the context of infections. Despite its importance for bacterial fitness, the QS regulon appears to be a common mutational target during long-term adaptation of P. aeruginosa in the host, natural environments and experimental evolutions. This raises the questions why such an important regulatory system is under selection and how mutations change the portfolio of QS-regulated traits. Here, we examine a set of 61 naturally evolved mutants to address these questions. We found that mutations involving the master regulator, LasR, resulted in an almost complete breakdown of QS, while mutations in RhlR and PqsR resulted in modulations of the QS regulon, where both the QS regulon structure and the QS-regulated trait portfolio changed. Our work reveals that natural selection drives diversification in QS activity patterns in evolving populations.

microbiology↗

bioRxiv2021

Pseudomonas aeruginosa reaches collective decisions via transient segregation of quorum sensing activities across cells

Bacteria engage in a cell-to-cell communication process called quorum sensing (QS) to coordinate expression of cooperative exoproducts at the group level. While population-level QS-responses are well studied, we know little about commitments of single cells to QS. Here, we use flow cytometry to track the investment of Pseudomonas aeruginosa individuals into their intertwined Las and Rhl QS-systems. Using fluorescent reporters, we show that QS gene expression (signal synthase, receptor and exoproduct) was heterogenous and followed a gradual instead of a sharp temporal induction pattern. The simultaneous monitoring of two QS genes revealed that cells transiently segregate into low receptor (lasR) expressers that fully commit to QS, and high receptor expressers that delay QS commitment. Our mathematical model shows that such gene expression segregation could mechanistically be spurred by transcription factor limitation. In evolutionary terms, temporal segregation could serve as a QS-brake to allow for a bet-hedging strategy in unpredictable environments.

microbiology↗