Biology subjects

Bajpai, S.

Publications and source records attributed to Bajpai, S..

8 recordsLinked to original sources

bioRxiv2026

Beyond the Axenic Culture Filtrate Secretome: BONCAT and conventional proteomics together reveal the Infection-associated secreted protein repertoire of Acinetobacter baumannii in the human lung Epithelial cell line A549

Acinetobacter baumannii (Ab) is an important opportunistic pathogen responsible for pneumonia, bloodstream infections, and sepsis. Although several virulence determinants have been characterized, the bacterial secreted protein repertoire associated with host cell infection remains incompletely understood. Conventional proteomic analyses of axenic cultures provide valuable information but cannot distinguish proteins synthesized before infection from those produced during host pathogen interactions. This study combined bioorthogonal noncanonical amino acid tagging (BONCAT) with conventional proteomics to characterize the infection associated Ab secreted protein repertoire recovered from human lung epithelial A549 cells. To achieve pathogen selective metabolic labelling, an Ab clinical isolate that had caused neonatal sepsis (Ab7) was engineered to express a methionyl tRNA synthetase variant, MetRSNLL (L10N, Y258L, H299L), capable of incorporating azidonorleucine (ANL) into newly synthesised bacterial proteins. Labelling conditions were optimized using methionine biosynthesis inhibitory amino acids, which reduced endogenous methionine availability without appreciably affecting bacterial growth. Efficient ANL incorporation was confirmed by flow cytometry, confocal microscopy, biotin streptavidin assays, and in gel fluorescence. Metabolic labelling also remained compatible with bacterial intracellular survival. Sequential labelling with azidohomoalanine (AHA) before infection and ANL during A549 infection enabled the temporal assignment of bacterial protein synthesis. Subsequent SDS PAGE fractionation and LC MS/MS identified 152 infection-associated proteins, including 23 containing experimentally detected amino acid analogue modifications. Among these, 13 were AHA only, nine were ANL only, and one contained both analogues. Notably, 117 proteins were not detected in either axenic reference proteome. The infection associated fraction exhibited enrichment of predicted signal peptide containing and outer membrane proteins, while functional annotation identified enrichment of bacterial secretion system components among infection-only proteins. These findings demonstrate the complementary strengths of BONCAT and conventional proteomics: BONCAT provides evidence of bacterial protein synthesis during infection, whereas conventional proteomics expands detection beyond proteins containing identifiable analogue modified peptides. Although extracellular recovery does not establish active secretion, the combined approach reveals a host associated bacterial protein repertoire extending beyond axenic observations. This framework supports future investigations into bacterial adaptation, host pathogen interactions, and the prioritization of candidate diagnostic biomarkers, subject to functional characterization and clinical validation. The study establishes a methodological foundation for investigating infection-associated protein synthesis and release in complex host pathogen environments.

microbiology↗

bioRxiv2025

A Flexible Quadruple-Stranded Helicate Demonstrates a Strong Binding Preference for DNA Three-Way Junctions by Induced-Fit

Nucleic acid junctions are key to many biological functions from recombination and repair to viral NA insertion, and are an attractive, functional biomolecular target. We describe a quadruple-stranded di-platinum helicate that binds both three-way (3WJ) and four-way DNA junctions (4WJ). This allows us to probe the relative importance of size and shape in junction-binder design. Despite the helicates tetragonal symmetry/shape being compatible with the 4WJ, microscale thermophoresis (MST), isothermal calorimetry (ITC) and gel electrophoresis competition experiments demonstrate that this metallo-supramolecule displays a stronger affinity for 3WJs (Kd = 12 nM) than for 4WJs (Kd > 4 {micro}M) and other DNA structures. The experimental findings are supported by molecular dynamics simulations which reveal the critical role of size. Whilst the open form of the 4WJ is promoted when the helicate is in the cavity, the helicates small size means it is unable to maintain {pi} contacts with all four junction base-pairs simultaneously. Although the helicate is slightly too large for the smaller 3WJ cavity, simulations and experiments show that it can open up the cavity (increasing the junctions hydrodynamic radius) by disrupting a base-pair. The flexible helicate also responds to the cavity upon binding by favouring one enantiomer and allowing the helicate to adopt a stable final structure inside the 3WJ that is an induced-fit of the two dynamic structures (supramolecule and DNA). This contrasts with previous lock-and-key examples of junction recognition and opens up new possibilities for how to design DNA and RNA junction-binding compounds. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/671622v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@175cabborg.highwire.dtl.DTLVardef@50f114org.highwire.dtl.DTLVardef@372e1org.highwire.dtl.DTLVardef@6b2960_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2022

Evolution of new variants of SARS-COV-2 during the pandemic: mutation limited or selection limited?

The recent pandemic caused by SARS-Cov-2 has witnessed an evolving succession of variants of the virus. While the phenomenon of invasion by immunity evading variants is known for other viruses such as influenza, the dynamics of the ecological and evolutionary process in the succession is little known. Since during the Covid-19 pandemic, large scale epidemiological data were collected and made available in the public domain, it is possible to seek answers to a number of evolutionary questions, which will also have public health implications. We list multiple alternative hypotheses about the origin and invasion of the variants and evaluate them in the light of epidemiological data. Our analysis shows that invasion by novel variants is selection limited and not mutation limited. Further novel variants are not the necessary and sufficient causes of the repeated waves during the pandemic. Rather there is substantial overlap between the conditions leading to a wave and those favoring selection of a partial immune evading variant. This is likely to lead to an association between invasion by new variant and the rise of a new wave. But the association is not sufficiently strong and does not support a causal role of the new variant. The dynamics of interaction between epidemiological processes and selection on viral variants have many public health implications that can guide future policies for effective control of infectious epidemics.

evolutionary biology↗

bioRxiv2022

Role of Delta-Notch signalling molecules on cell-cell adhesion in determining heterogeneous chemical and cell morphological patterning

Cell mechanics and motility are responsible for collective motion of cells that result in overall deformation of epithelial tissues. On the other hand, contact-dependent cell-cell signalling is responsible for generating a large variety of intricate, self-organized, spatial patterns of the signalling molecules. Moreover, it is becoming increasingly clear that the combined mechanochemical patterns of cell shape/size and signalling molecules in the tissues, for example, in cancerous and sensory epithelium, are governed by mechanochemical coupling between chemical signalling and cell mechanics. However, a clear quantitative picture of how these two aspects of tissue dynamics, i.e., signalling and mechanics, lead to pattern and form is still emerging. Although, a number of recent experiments demonstrate that cell mechanics, cell motility, and cell-cell signalling are tightly coupled in many morphogenetic processes, relatively few modeling efforts have focused on an integrated approach. We extend the vertex model of an epithelial monolayer to account for contact-dependent signalling between adjacent cells and between non-adjacent neighbors through long protrusional contacts with a feedback mechanism wherein the adhesive strength between adjacent cells is controlled by the expression of the signalling molecules in those cells. Local changes in cell-cell adhesion lead to changes in cell shape and size, which in turn drives changes in the levels of signalling molecules. Our simulations show that even this elementary two-way coupling of chemical signalling and cell mechanics is capable of giving rise to a rich variety of mechanochemical patterns in epithelial tissues. In particular, under certain parametric conditions, bimodal distributions in cell size and shape are obtained, which resemble experimental observations in cancerous and sensory tissues.

biophysics↗

bioRxiv2021

Real Time Face Recognition with limited training data: Feature Transfer Learning integrating CNN and Sparse Approximation

It is highly challenging to obtain high performance with limited and unconstrained data in real time face recognition applications. Sparse Approximation is a fast and computationally efficient method for the above application as it requires no training time as compared to deep learning methods. It eliminates the training time by assuming that the test image can be approximated by the sum of individual contributions of the training images from different classes and the class with maximum contribution is closest to the test image. The efficiency of the Sparse Approximation method can be further increased by providing high quality features as input for classification. Hence, we propose to integrate pre-trained CNN architecture to extract the highly discriminative features from the image dataset for Sparse classification. The proposed approach provides better performance even for one training image per class in complex environment as compared to the existing methods. Highlight of the present approach is the results obtained for LFW dataset with one and thirteen training images per class are 84.86% and 96.14% respectively, whereas the existing deep learning methods use a large amount of training data to achieve comparable results.

neuroscience↗

bioRxiv2020

Role of cell polarity dynamics and motility in pattern formation due to contact dependent signalling

A key challenge in biology is to understand how spatiotemporal patterns and structures arise during the development of an organism. An initial aggregate of spatially uniform cells develops and forms the differentiated structures of a fully developed organism. On the one hand, contact-dependent cell-cell signalling is responsible for generating a large number of complex, self-organized, spatial patterns in the distribution of the signalling molecules. On the other hand, the motility of cells coupled with their polarity can independently lead to collective motion patterns that depend on mechanical parameters influencing tissue deformation, such as cellular elasticity, cell-cell adhesion and active forces generated by actin and myosin dynamics. Although modelling efforts have, thus far, treated cell motility and cell-cell signalling separately, experiments in recent years suggest that these processes could be tightly coupled. Hence, in this paper, we study how the dynamics of cell polarity and migration influence the spatiotemporal patterning of signalling molecules. Such signalling interactions can occur only between cells that are in physical contact, either directly at the junctions of adjacent cells or through cellular protrusional contacts. We present a vertex model which accounts for contact-dependent signalling between adjacent cells and between non-adjacent neighbours through long protrusional contacts that occur along the orientation of cell polarization. We observe a rich variety of spatiotemporal patterns of signalling molecules that is influenced by polarity dynamics of the cells, relative strengths of adjacent and non-adjacent signalling interactions, range of polarized interaction, signalling activation threshold, relative time scales of signalling and polarity orientation, and cell motility. Though our results are developed in the context of Delta-Notch signalling, they are sufficiently general and can be extended to other contact dependent morpho-mechanical dynamics.

biophysics↗

bioRxiv2019

A comprehensive role of Toll-like receptors (TLRs) in diabetic wound healing

Diabetes is marked by delayed wound healing response and prolonged phase of inflammation. Toll-like receptors (TLRs) are the key pathogen recognition receptors known to regulate inflammation in wound healing. Therefore, we aim to investigate the role of TLRs in delayed healing of diabetic wounds. TLR (1-9) expression studies were conducted using J774 macrophage cell line. Further, primary macrophages were isolated from wound tissues of db/db mice, subjected to RT-PCR and western blot analysis. The RT-PCR expression of TLRs revealed that expression of TLR2, TLR4, TLR5, TLR6, TLR7 and TLR8 were significantly upregulated in macrophage cells, cultured in high glucose medium. Expression of TLR 1-9 were significantly upregulated in wound tissues of db/db mice. However, TLR1, TLR2 and TLR4, TLR6, TLR7 were only found upregulated in the primary macrophages. Only TLR2 and TLR4 exhibited significantly increased protein expression. Further, TLR2 and TLR4 inhibition by OxPAPC (1-palmitoyl-2-arachidonyl-sn-glycero-3-phosphorylcholine) impregnated hydrogels, resulted in a significantly increased rate of wound healing in db/db mice via decreasing the significant levels of TNF- and IL-1{beta}. These results show that increased TLR 2 and TLR 4 expression underlies delayed wound healing in diabetes and a hydrogel impregnated with OxPAPC may be a promising therapeutic strategy for the management of diabetic wounds. Our study goes closer in understanding the molecular mechanism and provides a novel treatment method in diabetic wounds.

immunology↗

bioRxiv2019

Serum proteomic approach for differentiation of frail and non-frail elderly

Frail elderly is very common in Indian society and extremely difficult to manage in the clinical practice. Blood proteomic study may able to improve the specific diagnostic profiles and therapeutic templates for improving quality of life in elderly. The purpose of present study is to differentiate between frail and non-frail elderly on the basis of serum markers. The proteomic profile of 10 frail and 10 non-frail elderly diagnosed according to deficit accumulation model of Rockwood was identified by 2D-electrophoresis and analyzed using ImageMaster 2DPlatinum7.0 software. The proteins were identified by MALDI-TOF/TOF and performed gene ontology study by PANTHER 7.0 software. Overall 105 spots were identified in the study groups. In frail 22spots and in non-frail 12spots were found to be differentially expressed. Mass spectroscopy analysis of 13 spots showed up-regulated Haptoglobin, Serum amyloidA1, TRAK1, sp110, NLRC3, MMP12, Mortalin, NDK3 and downregulated PSRC1, NKG2A proteins in frail elderly. The differential expression of proteins in frailty are mostly associated with pro-inflammation and is well-known that frailty syndrome increases all inflammatory parameters. It can be summarized from the present proteomic study that these proteins can be used as potential biomarkers for early detection of frailty in the elderly.

biophysics↗