Biology subjects

Shetty, S.

Publications and source records attributed to Shetty, S..

22 records · Page 2Linked to original sources

bioRxiv2019

Effect of temperature and agitation rate variation on the growth of NS0 cell line in monoclonal antibody production

The quality and yield of the monoclonal antibodies produced in a cGMP environment is heavily influenced by the bioprocess-related parameters which impact the cell growth and metabolism of the mammalian cell cultures. This research report describes a study conducted to examine the effects of varying temperature and RPM set points on viable cell density and viability of NS0 cultures. All cultures were grown in 250 mL shake flasks (working vol. 100 mL). To separately analyze the effects of temperature and agitation rate on NS0 cell metabolism, flask stage cultures were evaluated in triplicates at two cultivation temperatures (36 {degrees}C and 38 {degrees}C) and two agitation rates (120 RPM and 160 RPM) while controls were maintained at 37 {degrees}C and 140 RPM for both the conditions using an incubator. Flasks were sampled every 24 h and analyzed for viable cell density and % viability. Additional data was collected on pH, pO2, pCO2, osmolality, glucose, lactate, glutamate and glutamine levels in the culture. It was observed that variations in temperature has the greatest effect on viable cell density and viability and varying agitation rates had minimal effect on growth of cultures. A temperature set point of 38 {degrees}C is detrimental to the culture growth. The control set points proved to be optimal for this process.

cell biology↗

bioRxiv2018

Novel KCNJ10 mutation identified in a SeSAME family compromise channel function and impairs Drosophila locomotor behavior

Dysfunction in inwardly-rectifying potassium channel Kir4.1 has been implicated in SeSAME syndrome, an autosomal-recessive (AR), rare, multi-systemic disorder. However, not all neurological, intellectual disability and comorbid phenotypes in SeSAME syndrome can be mechanistically linked solely to Kir4.1 dysfunction. We therefore performed whole exome sequencing and identified additional genetic risk-elements that might exert causative effects either alone or in concert with Kir4.1 in a family diagnosed with SeSAME syndrome. Two variant prioritization pipelines based on AR inheritance and runs of homozygosity (ROH), identified two novel homozygous variants in KCNJ10 and PI4KB and five rare homozygous variants in PVRL4, RORC, FLG2, FCRL1, NIT1 and one common homozygous variant in HSPA6 segregating in all four patients. The novel mutation in KCNJ10 resides in the cytoplasmic domain of Kir4.1, a seat of phosphatidyl inositol bisphosphate (PIP2) binding. The mutation altered the subcellular localization and stability of Kir4.1 in patient-specific lymphoblastoid cells (LCLs) compared to parental controls. Barium-sensitive endogenous K+ currents in patient-specific LCLs using whole-cell patch clamp electrophysiology revealed membrane depolarization and defects in inward K+ ion conductance across the membrane, thereby suggesting a loss-of-function effect of KCNJ10 variant. Altogether our findings implicate the role of new genes in SeSAME syndrome without electrolyte imbalance and thereby speculate the regulation of Kir4.1 channel activity by PIP2 and integrin-mediated adhesion signaling mechanisms.

neuroscience↗

bioRxiv2018

Predicting Brain Age Using Structural Neuroimaging and Deep Learning

Early detection of age-related diseases will greatly benefit from a model of the underlying biological aging process. In this paper, we develop a brain-age predictor by using structural magnetic resonance imaging (SMRI) and deep learning and evaluate the predicted brain age as a marker of brain-aging in Alzheimer's disease. Our approach does not require any domain knowledge in that it trains end-to-end on the SMRI image itself, and has been validated on real SMRI data collected from elderly subjects. We developed two different models by using convolutional neural network (CNN) based regression and bucket classification to predict brain ages from SMRI images. Our models achieved root mean squared errors (RMSE) of 5.54 and 6.44 years in predicting brain ages of healthy subjects. Further analysis showed that there is a substantial difference between the predicted brain ages of cognitively impaired and healthy subjects with similar chronological ages.

bioengineering↗

bioRxiv2018

Gut microbiota features of the geographically diverse Indian population

Population-level microbial profiling allows for identifying the overarching features of the microbiome. Knowledge of population specific base-line gut microbiome features is important due to the widely reported impact of geography, lifestyle and dietary patterns on the microbiome composition, structure and function. Here, the gut microbiota of more than 1000 subjects across the length and breadth of India is presented. The publicly available 16S rRNA gene profiling data of faecal microbiota from the Landscape Of Gut Microbiome - Pan-India Exploration (LogMPIE) study representing 14 major cities, covering populations from northern, southern, eastern and western part of India analyzed. Majority of the dominant OTUs belonged to the Firmicutes, Bacteroidetes and Proteobacteria phyla. The rarer fraction was comprised of OTUs mainly from the phyla Verrucomicrobia and Spirochaetes. The median core size was estimated to consist of 12 OTUs (>80% prevalence) dominated by representing genera Prevotella, Faecalibacterium, Bacteroides, Roseburia, Megasphaera, Eubacterium and Gemmiger. Geographic location explained majority of the variation in the gut microbiota community structure. The observations of the present study support the previous reports of Prevotella dominance in the Indian population. The Prevotella/Bacteroides ratio was high for the overall population irrespective of geographic location and did not correlate with BMI or age of the participants. Despite a rapid transition towards a western lifestyle, high prevalence of Treponema in the Indian gut microbiota suggests that the urban population still harbors signatures of the traditional gut microbiome. The results presented here improve the knowledge of baseline microbiota in the Indian population across the length and breadth of the country. This study provides a base for future studies which need to incorporate numerous other confounding factors and their impact on the observed characteristics of the Indian gut microbiome.

microbiology↗