Biology subjects

Kar, P.

Publications and source records attributed to Kar, P..

11 recordsLinked to original sources

bioRxiv2026

Entropy-based integration index for quantifying network integration in resting-state functional MRI

Independent component analysis (ICA) is widely used in resting-state fMRI to identify large-scale functional networks; however, existing approaches provide limited means of quantifying how network representations are distributed across independent components. We introduce an entropy-based network integration framework that characterizes the organizational architecture of canonical resting-state networks by quantifying the distribution of ICA-derived functional contributions within Yeo atlas networks. Spatial overlap between independent components and network templates is normalized to generate a probability distribution, from which Shannon entropy and a normalized integration index are derived. The resulting metric provides a continuous measure of network representational integration, ranging from specialized configurations dominated by a small number of components to distributed configurations involving multiple functional modes. The framework was evaluated and validated using resting-state fMRI data from healthy controls, Parkinsons disease patients with normal cognition, and Parkinsons disease patients with mild cognitive impairment. Global entropy and integration measures were complemented by network-specific analyses, dominance profiling, principal component analysis (PCA), and multivariate centroid-distance assessments. The proposed framework revealed selective alterations in Ventral Attention and Limbic network organization associated with cognitive-status differences, while preserving overall within-group heterogeneity. Group-wise PCA independently further identified these networks as major contributors to altered network organization, and centroid-distance analyses demonstrated that observed differences reflected coherent shifts in network architecture rather than increased variability. By quantifying the distribution of network representations across ICA-derived functional modes, this framework provides a simple, interpretable, and generalizable measure of large-scale brain organization, offering a complementary approach for studying network reorganization in health and disease.

neuroscience↗

bioRxiv2026

Inference of elevated mutation rates and variant effects using 700k exomes

Genomic sequencing is now widely accessible for genetic diagnostics and is emerging as a component of newborn screening. This technological development generates the need to characterize incoming mutations, create comprehensive datasets of genes causing rare Mendelian disorders, and identify pathogenic variants. Large-scale exome sequencing datasets such as Genome Aggregation Database (gnomAD) have been assembled to help address these challenges. The recent release of gnomAD (v4; n = 730,947) uncovers millions of rare coding variants, many of which have arisen more than once by independent recurrent mutations in the rapidly growing recent human population. Here, we use newly developed theoretical understanding of sampling properties of rare variants to estimate key population genetics parameters of practical importance to human genetics such as demography history, mutation rate, and selection. Solely relying on population data, our method Population Inferred Estimates of Selection (PIES) identifies novel genes with loss-of-function mutational hotspots likely due to selection in spermatogonia. PIES efficiently estimates selection coefficients for heterozygous loss-of-function variants. Combining population genetics inference with variant effect predictors, PIES predicts pathogenic missense mutations and improves variant prioritization for genetic diagnostics and newborn screening.

genetics↗

bioRxiv2024

Are cell length and volume interchangeable in cell cycle analysis?

Cell length has been used as a proxy for cell size in cell cycle modeling studies. A previous study, however, brought into question the validity of this assumption, noting that correlations between cell lengths can be different from those involving cell volume if cell width fluctuations are taken into account. If cell volume is regulated, data analysis involving cell lengths will lead to an incorrect inference of the cell size control mechanism. We used conditional correlation of length variables conditioned upon radius variables to elucidate the underlying volume control mechanism. Using the conditional correlation on previous mother machine datasets measuring lengths at birth and division, and the cell radius for multiple cells, we find that the cell volume control strategy is consistent with an adder model. Further, using the conditional correlation, we conclude that measurement noise constitutes a significant portion of the radius variability in the experimental datasets. To conclude, cell length and cell volume can often be used interchangeably owing to small cell width fluctuations.

biophysics↗

bioRxiv2024

Determining the rate-limiting processes for cell division in Escherichia coli

A critical cell cycle checkpoint for most bacteria is the onset of constriction when the septal peptidoglycan synthesis starts. According to the current understanding, the arrival of FtsN to midcell triggers this checkpoint in Escherichia coli. Recent structural and in vitro data suggests that recruitment of FtsN to the Z-ring leads to a conformational switch in actin-like FtsA, which links FtsZ protofilaments to the cell membrane and acts as a hub for the late divisome proteins. Here, we investigate this putative pathway using in vivo measurements and stochastic cell cycle modeling. Quantitatively upregulating protein concentrations and determining the resulting division timings shows that FtsN and FtsA numbers are not rate-limiting for the division in E. coli. However, at higher overexpression levels, they affect divisions: FtsN by accelerating and FtsA by inhibiting them. At the same time, we find that the numbers of FtsZ in the cell are rate-limiting for cell divisions in addition to other processes. Altogether, these findings suggest that instead of FtsN, FtsZ protofilaments drive the conformational switch of FtsA and lead to the onset of constriction. Our data is also suggestive that FtsA minirings are not present at any significant numbers in wild-type cells.

cell biology↗

bioRxiv2023

PARP14 is a PARP with both ADP-ribosyl transferase and hydrolase activities

PARP14 is a mono-ADP-ribosyl transferase involved in the control of immunity, transcription and DNA replication stress management. However, little is known about the ADP-ribosylation activity of PARP14, including its substrate specificity or how PARP14-dependent ADP-ribosylation is reversed. Here we show that PARP14 is dual function enzyme with both ADP-ribosyl transferase and hydrolase activity acting on both protein and nucleic acid substrates. In particular, we show that the PARP14 macrodomain 1 is an active ADP-ribosyl hydrolase. We also demonstrate hydrolytic activity for the first macrodomain of PARP9. We reveal that expression of a PARP14 mutant with the inactivated macrodomain 1 results in a dramatic increase in mono(ADP-ribosyl)ation of proteins in human cells, including PARP14 itself and antiviral PARP13. Moreover, we demonstrate that the closely related hydrolytically active macrodomain of SARS2 Nsp3, Mac1, efficiently reverses PARP14 ADP-ribosylation in vitro and in cells, supporting the evolution of viral macrodomains to counteract PARP14-mediated antiviral response. TeaserPARP14 is an antiviral PARP that combines ADP-ribosylation writer, reader and eraser functions in one polypeptide.

cell biology↗

bioRxiv2023

Mycobacterium tuberculosis grows linearly at the single-cell level with larger variability than model organisms

The ability of bacterial pathogens to regulate growth is crucial to control homeostasis, virulence, and drug response. Yet, we do not understand the growth and cell cycle behaviors of Mycobacterium tuberculosis (Mtb), a slow-growing pathogen, at the single-cell level. Here, we use time-lapse imaging and mathematical modeling to characterize these fundamental properties of Mtb. Whereas most organisms grow exponentially at the single-cell level, we find that Mtb exhibits a unique linear growth mode. Mtb growth characteristics are highly variable from cell-to-cell, notably in their growth speeds, cell cycle timing, and cell sizes. Together, our study demonstrates that growth behavior of Mtb diverges from what we have learned from model bacteria. Instead, Mtb generates a heterogeneous population while growing slowly and linearly. Our study provides a new level of detail into how Mtb grows and creates heterogeneity, and motivates more studies of growth behaviors in bacterial pathogens.

microbiology↗

bioRxiv2021

To bin or not to bin: analyzing single-cell growth data

Collection of high-throughput data has become prevalent in biology. Large datasets allow the use of statistical constructs such as binning and linear regression to quantify relationships between variables and hypothesize underlying biological mechanisms based on it. We discuss several such examples in relation to single-cell data and cellular growth. In particular, we show instances where what appears to be ordinary use of these statistical methods leads to incorrect conclusions such as growth being non-exponential as opposed to exponential and vice versa. We propose that the data analysis and its interpretation should be done in the context of a generative model, if possible. In this way, the statistical methods can be validated either analytically or against synthetic data generated via the use of the model, leading to a consistent method for inferring biological mechanisms from data. On applying the validated methods of data analysis to infer cellular growth on our experimental data, we find the growth of length in E. coli to be non-exponential. Our analysis shows that in the later stages of the cell cycle the growth rate is faster than exponential.

microbiology↗

bioRxiv2021

Replication-related control over cell division in Escherichia coli is growth-rate dependent

How replication and division processes are coordinated in the cell cycle is a fundamental yet poorly understood question in cell biology. In Escherichia coli different data sets and models have supported a range of conclusions from one extreme where these two processes are tightly linked to another extreme where these processes are completely independent of each other. Using high throughput optical microscopy and cell cycle modeling, we show that in slow growth conditions replication and division processes are strongly correlated, indicating a significant coupling between replication and division. This coupling weakens as the growth rate of cells increases. Our data suggest that the underlying control mechanism in slow growth conditions is related to unreplicated chromosome blocking the onset of constriction at the midcell. We show that the nucleoid occlusion protein SlmA does not play a role in this process and neither do other known factors involved in positioning bacterial Z-ring relative to the chromosome. Altogether this work reconciles different ideas from the past and brings out a more nuanced role of replication in controlling the division process in a growth-rate dependent manner.

cell biology↗

bioRxiv2021

Association between breastfeeding during infancy and white matter microstructure in early childhood

IntroductionAssociations between breastfeeding and brain development, in the context of child, perinatal, and sociodemographic variables, remain unclear. This study investigates whether exclusive breastfeeding for the first 6 months and total duration of any breastfeeding are associated with brain white matter microstructure in young children. MethodsThis study included a sample of 83 mothers and 85 typically developing children (42 males). Children underwent their first diffusion tensor imaging scan between ages 2.34-6.97 years; some children returned multiple times, providing a total of 331 datasets. Feeding information was collected from the mothers at 3, 6, and 12 months postpartum and at their childs scan to calculate breastfeeding status at 6 months (exclusive or not) as well as total duration of any breastfeeding. Linear regression was used to investigate associations between breastfeeding exclusivity/duration and fractional anisotropy (FA, a measure sensitive to myelination/axonal packing/fibre coherence) for the whole brain and 10 individual white matter tracts. ResultsBreastfeeding exclusivity and duration were associated with global and regional white matter microstructure, even after controlling for perinatal and sociodemographic factors. Greater exclusivity was associated with higher FA in females and lower FA in males. ConclusionsThese findings suggest white matter differences associated with breastfeeding that differ by sex. These may stem from different trajectories in white matter development between males and females in early childhood and suggest possible long-term white matter differences associated with breastfeeding.

neuroscience↗

bioRxiv2021

White Matter Alterations in Young Children with Prenatal Alcohol Exposure

Prenatal alcohol exposure (PAE) can lead to cognitive, behavioural, and social-emotional challenges. Previous neuroimaging research has identified alterations to brain structure in newborns, older children, adolescents, and adults with PAE; however, little is known about brain structure in young children. Extensive brain development takes place during early childhood; therefore, understanding the neurological profiles of young children with PAE is critical for early identification and effective intervention. We studied 54 children (5.21{+/-}1.11 years; 27 males) with confirmed PAE compared to 54 age- and sex-matched children without PAE. Children underwent diffusion tensor imaging between 2 and 7 years of age. Mean fractional anisotropy (FA) and mean diffusivity (MD) were obtained for 10 major white matter tracts, along with tract volume, axial and radial diffusivity (AD, RD). A univariate analysis of covariance was conducted to test for group differences (PAE vs. control) controlling for age, sex and tract volume. Our results reveal white matter microstructural differences between young children with PAE and unexposed controls. The PAE group had higher FA and/or lower MD (as well as lower AD and RD) in the genu and the body of the corpus callosum, as well as the bilateral uncinate fasciculus and pyramidal tracts. Our findings align with studies of newborns with PAE finding lower AD, but contrast those in older populations with PAE, which consistently report lower FA and higher MD. These findings may reflect premature development of white matter that may then plateau too early, leading to the lower FA/higher MD observed at older ages.

neuroscience↗

bioRxiv2017

Nitric oxide sensing by chlorophyll a

Nitric oxide (NO) acts as a signalling molecule that has direct and indirect regulatory roles in various functional processes in biology, though in plant kingdom its role is relatively unexplored. One reason for this is the fact that sensing of NO is always challenging. There are very few probes that can classify the different NO species. The present paper proposes a simple but straightforward way for sensing different NO species using chlorophyll, the source of inspiration being hemoglobin that serves as a NO sink in most mamalian system. The proposed method is able to classify NO from DETA-NONOate or (Z)-1-[N-(2-aminoethyl)-N-(2-ammonioethyl) amino] diazen-1-ium-1,2-diolate, nitrite, nitrate and S-nitrosothiol or SNO. This discrimination is carried out by chlorophyll a (chl a) at nano molar (nM) order of sensitivity and at 293K to 310K. Molecular docking reveals the differential binding behaviour of NO and SNO with chlorophyll, the predicted binding affinity matching with the experimental observation. Additional expreiments with diverse range of cyanobacteria reveals that apart from spectroscopic approach the proposed sensing module can be used in microscopic inspection of NO speices. Binding of NO is sensitive to tempertaure and static magnetic field. This provides additional support to the involvement of the porphyrin ring structure to the NO sensing process. This also broadens the scope of the sensing methods as hinted in the text.

bioengineering↗