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Biology subjects

Nagaraj, N.

Publications and source records attributed to Nagaraj, N..

7 recordsLinked to original sources

Females use multiple cues to assess competition for egg-laying decisions

Animals deploy a wide suite of behavioural responses to reduce fitness costs related to competition. One common strategy is spatial avoidance of resource patches associated with high competition and this involves a need to accurately assess the level of competition associated with patches. Although well-studied in the context of predation risk (alarm cues vs kairomones), we lack in our understanding of how inputs from multiple types of cues are used for assessing the level of conspecific competition. We tested how Aedes aegypti females select sites for oviposition when they encounter multiple types of cues from varying densities of conspecifics. We hypothesised that females perceive conspecific young within these sites as potential competition for their offspring, and tailor their response to the type and level of competition. Through binary choice trials, we assessed female oviposition behaviour in response to a gradient in two types of conspecific cues - egg and larvae. Our results indicate that female response was sensitive to the type of cue. Females showed attraction towards pools with low densities of both egg and larval conspecifics indicating conspecific cueing and the strength of response was stronger towards egg cues. However, this attraction response disappeared at high densities of conspecifics (both egg and larvae) suggesting that the resulting trade-off between benefits from conspecific cueing and costs of competition likely shapes oviposition site selection responses. The broad nature of the oviposition response was similar toward both egg and larval cues, but there were fine level differences in responses towards egg and larvae that depended on the conspecific density level. Our study shows that animals are under selection to use multiple cues to assess conspecific competition to minimise the costs of competition.

animal behavior and cognition↗

Rod-shaped microglia interact with neuronal dendrites to regulate cortical excitability in TDP-43 related neurodegeneration

Motor cortical hyperexcitability is well-documented in the presymptomatic stage of amyotrophic lateral sclerosis (ALS). However, the mechanisms underlying this early dysregulation are not fully understood. Microglia, as the principal immune cells of the central nervous system, have emerged as important players in sensing and regulating neuronal activity. Here we investigated the role of microglia in the motor cortical circuits in a mouse model of TDP-43 neurodegeneration (rNLS8). Utilizing multichannel probe recording and longitudinal in vivo calcium imaging in awake mice, we observed neuronal hyperactivity at the initial stage of disease progression. Spatial and single-cell RNA sequencing revealed that microglia are the primary responders to motor cortical hyperactivity. We further identified a unique subpopulation of microglia, rod-shaped microglia, which are characterized by a distinct morphology and transcriptional profile. Notably, rod-shaped microglia predominantly interact with neuronal dendrites and excitatory synaptic inputs to attenuate motor cortical hyperactivity. The elimination of rod-shaped microglia through TREM2 deficiency increased neuronal hyperactivity, exacerbated motor deficits, and further decreased survival rates of rNLS8 mice. Together, our results suggest that rod-shaped microglia play a neuroprotective role by attenuating cortical hyperexcitability in the mouse model of TDP-43 related neurodegeneration.

neuroscience↗

Accurate and automated high-coverage identification of chemically cross-linked peptides with MaxLynx

Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the 3D structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to non-cleavable and MS-cleavable cross linkers. For both we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For non-cleavable peptides, we implemented a novel di-peptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the di-peptide individually. A posterior error probability based on total and partial scores is used to control false discovery rates. For MS-cleavable cross linkers a scoring of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D-peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace manual filtering of identifications, which is often necessary when using other pipelines. On benchmark datasets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross linkers as well as on a proteome-wide dataset of cross-linked D. melanogaster cell lysate. The workflow also supports ion-mobility enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra and is freely available at https://www.maxquant.org/.

bioinformatics↗

Automatic Identification of SARS Coronavirus using Compression-Complexity Measures

AO_SCPLOWBSTRACTC_SCPLOWFinding vaccine or specific antiviral treatment for global pandemic of virus diseases (such as the ongoing COVID-19) requires rapid analysis, annotation and evaluation of metagenomic libraries to enable a quick and efficient screening of nucleotide sequences. Traditional sequence alignment methods are not suitable and there is a need for fast alignment-free techniques for sequence analysis. Information theory and data compression algorithms provide a rich set of mathematical and computational tools to capture essential patterns in biological sequences. In 2013, our research group (Nagaraj et al., Eur. Phys. J. Special Topics 222(3-4), 2013) has proposed a novel measure known as Effort-To-Compress (ETC) based on the notion of compression-complexity to capture the information content of sequences. In this study, we propose a compression-complexity based distance measure for automatic identification of SARS coronavirus strains from a set of viruses using only short fragments of nucleotide sequences. We also demonstrate that our proposed method can correctly distinguish SARS-CoV-2 from SARS-CoV-1 viruses by analyzing very short segments of nucleotide sequences. This work could be extended further to enable medical practitioners in automatically identifying and characterizing SARS coronavirus strain in a fast and efficient fashion using short and/or incomplete segments of nucleotide sequences. Potentially, the need for sequence assembly can be circumvented. NoteThe main ideas and results of this research were first presented at the International Conference on Nonlinear Systems and Dynamics (CNSD-2013) held at Indian Institute of Technology, Indore, December 12, 2013. In this manuscript, we have extended our preliminary analysis to include SARS-CoV-2 virus as well.

bioinformatics↗

Proteomics identifies signal peptide features determining the substrate specificity in human Sec62/Sec63-dependent ER protein import

In mammalian cells one-third of all polypeptides are integrated into the membrane or translocated into the lumen of the endoplasmic reticulum (ER) via the Sec61-channel. While the Sec61-complex facilitates ER-import of most precursor polypeptides, the Sec61-associated Sec62/Sec63-complex supports ER-import in a substrate-specific manner. So far, mainly posttranslationally imported precursors and the two cotranslationally imported precursors of ERj3 and prion protein were found to depend on the Sec62/Sec63-complex in vitro. Therefore, we determined the rules for engagement of Sec62/Sec63 in ER-import in intact human cells using a recently established unbiased proteomics approach. In addition to confirming ERj3, we identified twenty-two novel Sec62/Sec63-substrates under these in vivo-like conditions. As a common feature, those previously unknown substrates share signal peptides with comparatively longer but less hydrophobic H-region and lower C-region polarity. Further analyses with four substrates, and ERj3 in particular, revealed the combination of a slowly-gating signal peptide and a downstream translocation-disruptive positively charged cluster of amino acid residues as decisive for the Sec62-/Sec63-requirement. In the case of ERj3, these features were found to be responsible for an additional BiP-requirement and to correlate with sensitivity towards the Sec61-channel inhibitor CAM741. Thus, the human Sec62/Sec63-complex may support Sec61-channel opening for precursor polypeptides with slowly-gating signal peptides by direct interaction with the cytosolic amino-terminal peptide of Sec61 or via recruitment of BiP and its interaction with the ER-lumenal loop 7 of Sec61. These novel insights into the mechanism of human ER protein import contribute to our understanding of the etiology of SEC63-linked Polycystic Liver Disease. DatabasesThe mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (http://www.ebi.ac.uk/pride/archive/projects/Identifiers) with the dataset identifiers: PXD008178, PXD011993, and PXD012078. Supplementary information was deposited at Mendeley Data under the DOI:10.17632/6s5hn73jcv.1 (http://dx.doi.or/10.17632/6s5hn73jcv.1).

biochemistry↗

Distinguishing Different Levels Of Consciousness using a Novel Network Causal Activity Measure

Characterizing consciousness, the inner subjective feeling that is present in every experience, is a hard problem in neuroscience, but has important clinical implications. A leading neuro-scientific approach to understanding consciousness is to measure the complex causal neural interactions in the brain. Elucidating the complex causal interplay between cortical neural interactions and the subsequent network computations is very challenging. In this study, we propose a novel quantitative measure of consciousness - Network Causal Activity - using a recently proposed Compression-Complexity Causality measure to analyze electrocorticographic signals from the lateral cortex of four monkeys during two states of consciousness (awake and anaesthesia). Our results suggest that Network Causal Activity is consistently higher in the awake state as compared with anaesthesia state for all the monkeys.

bioengineering↗

Cross-linking/Mass Spectrometry: A Community-Wide, Comparative Study Towards Establishing Best Practice Guidelines

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has largely increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats that are generally accepted in the field and that have shown to lead to high-quality results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. From the results obtained, common protocols will be established. Our study serves as basis for establishing best practice guidelines in the field for conducting cross-linking experiments, performing data analysis, and reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

biochemistry↗