Biology subjects

Srinivasan, L.

Publications and source records attributed to Srinivasan, L..

4 recordsLinked to original sources

bioRxiv2024

A spatio-temporaral atlas of the growing brain for fMRI studies

Spatio-temporal atlases of the growing brain can help when building models of brain development, not only for anatomical structure, but also for the changing patterns of activation within the brain. In this paper, we build such an age-dependent atlas using registrations among a large number of anatomical datasets, acquired from neonatal subjects of different ages, and followed by kernel-based regression. fMRI activation data are then registered to this atlas to build a model of the development of brain networks, such as the default and motor networks, at this early age.

neuroscience↗

bioRxiv2022

Spatio-temporal analysis of LC3 association to Mycobacterium tuberculosis phagosomes in human macrophages

Autophagy plays a crucial role in the host response to Mycobacterium tuberculosis (Mtb) infection, yet the dynamics and regulation of autophagy induction on mycobacterial phagosomes remain partially understood. In this study, we employed time-lapse confocal microscopy to investigate in real time the recruitment of LC3B (LC3), a key autophagy marker, to Mtb-containing vacuoles (MCVs) at the single cell level with our newly developed workflow for single cell and single MCV tracking and fluorescence quantification. The results reveal that approximately 70% of MCVs exhibited LC3 recruitment but was lost in about 40% of those MCVs. The LC3 recruitment to MCVs displayed a high variability in timing that was independent of the size of the MCV or the bacterial burden. Most notably, the LC3-positive MCVs did not acidify, indicating that LC3 recruitment does not necessarily lead to the formation of mature autophagolysosomes. In addition, interferon-gamma (IFN-{gamma}) pre-treatment did not affect LC3 recruitment frequency or autophagosome maturation, but increased the susceptibility of the macrophage to Mtb-induced cell death. Instead, LC3 recruitment and lysotracker staining were mutually exclusive events alternating on some MCVs multiple times showing a new reversible aspect of this autophagy response. It also suggested a role of autophagy in membrane repair of the MCV. Consistently, LC3 recruitment was strongly associated with galectin-3 and oxysterol-binding protein 1 staining, indicating a correlation with membrane damage and repair mechanisms. However, knockdown of ATG7 did not impact membrane repair, suggesting that autophagy is not directly involved in this process but is coregulated by the membrane damage of MCVs. In summary, our findings provide novel insights into the dynamic and variable nature of LC3 recruitment and autophagy to the MCVs over time during Mtb infection. Our data suggests that there is no major role of autophagy in cell autonomous defense against Mtb nor membrane repair of the MCV in human macrophages. However, the combined dynamics of LC3 recruitment and Lysoview staining emerged as promising markers for future research focused on directly investigating the damage and repair processes of phagosomal membranes.

cell biology↗

bioRxiv2020

Sequence-based prediction of vaccine targets for inducing T cell responses to SARS-CoV-2 utilizing the bioinformatics predictor RECON

BackgroundThe ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Consistent with observations for SARS-CoV, a closely related coronavirus responsible for the 2003 SARS outbreak, early reports identify a protective role for both humoral and cell-mediated immunity for SARS CoV-2. MethodsIn this study, we leveraged HLA-I and HLA-II T cell epitope prediction tools from RECON(R) (Real-time Epitope Computation for ONcology), our bioinformatic pipeline that was developed using proteomic profiling of individual HLA-I and HLA-II alleles to predict rules for peptide binding to a diverse set of such alleles. We applied these binding predictors to viral genomes from the Coronaviridae family, and specifically to identify SARS-CoV-2 T cell epitopes. ResultsTo test the suitability of these tools to identify viral T cell epitopes, we first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then use our HLA-I and HLA-II predictors to identify 11,776 HLA-I and 7,991 HLA-II candidate binding peptides across all 12 open reading frames (ORFs) of SARS-CoV-2. This extensive list of identified candidate peptides is driven by the length of the ORFs and the significant number of HLA-I and HLA-II alleles that we are able to predict (74 and 83, respectively), providing over 99% coverage for the US, European and Asian populations, for both HLA-I and HLA-II. From our SARS-CoV-2 predicted peptide-HLA-I allele pairs, 368 pairs identically matched previously reported pairs in the ViPR database, originating from other forms of coronaviruses. 320 of these pairs (89.1%) had a positive MHC-binding assay result. This analysis reinforces the validity our predictions. ConclusionsUsing this bioinformatic platform, we identify multiple putative epitopes for CD4+ and CD8+ T cells whose HLA binding properties cover nearly the entire population and thus may be effective when included in prophylactic vaccines against SARS-CoV-2 to induce broad cellular immunity.

bioinformatics↗

bioRxiv2019

Population-scale prediabetic assessment using HbA1c from menstrual blood

CDC-recommended diabetes prevention programs aim to detect and reverse disease in the one-third of Americans with prediabetes, but high-compliance serial assessment of percent hemoglobin A1c (HbA1c) remains a barrier to delivering this vision at population scale. Venous phlebotomy is challenging for busy or resource-constrained patients.\n\nIn this paper, we introduce the first-ever quantitative diagnostic test based on menstrual fluid, which allows HbA1c quantification from self-collected mailed tampons.We demonstrate that menstrual HbA1c is comparable to venous HbA1c in the diagnosis of prediabetes with the standard threshold of 5.7. We also demonstrate accuracy, precision, stability, and interference testing. Finally, surveying subjects reveals strong preference for menstrual HbA1c in quarterly testing. These findings suggest that menstrual HbA1c can be a key tool in addressing prediabetes at population scale.

pathology↗