Biology subjects

Goyal, J.

Publications and source records attributed to Goyal, J..

4 recordsLinked to original sources

bioRxiv2026

Standardising Cellulose Production From Acetobacter diazotrophicus

Bacterial cellulose (BC) is a biopolymer that comes from natural sources. It has high purity, crystallinity, mechanical strength, and biocompatibility, which makes it suitable for various biomedical and industrial uses. Unlike plant cellulose, BC does not contain lignin or hemicellulose. This results in better material quality and simpler processing. However, producing BC on a large scale is limited by high production costs, expensive culture media, and dependence on a few bacterial strains. It is essential to find cost-effective production methods and alternative microbial sources to expand its commercial use. This study looked at the cellulose-producing ability of Acetobacter diazotrophicus, a safe and relatively unexplored bacterium, under different growth conditions. We compared bacterial growth and cellulose production using Hestrin-Schramm (HS) medium, the standard for BC production, and LB supplemented with glucose (LB+Glucose), which we explored as a more affordable option. We analyzed growth rates, inoculum age, and pH levels to find the best conditions for cellulose production. We observed faster bacterial growth in HS medium, with a doubling time of 3.906 hours, compared to 6.241 hours in LB+Glucose medium. Cellulose production was greatly affected by inoculum age, with successful synthesis from cultures that were agitated for 36 to 40 hours. The highest cellulose yield was at pH 6.0 in HS medium (4.6 mg/mL) and at pH 5.5 in LB+Glucose medium (3.6 mg/mL). FTIR analysis confirmed the presence of characteristic functional groups of bacterial cellulose. These results suggest that Acetobacter diazotrophicus is a promising and cost-effective option for producing bacterial cellulose and highlight the importance of medium composition, inoculum age, and pH for optimizing production.

microbiology↗

bioRxiv2026

Evaluation of Significance of SERPINA3 and SPP1 in Driving Glioma Progression Through Dysregulation of Brain Inflammatory Pathway

Glioma is a highly aggressive malignancy with a poor prognosis, particularly in grade IV glioblastoma. The monitoring of disease progression remains challenging due to high heterogeneity in the tumour and a lack of progressive markers to keep track of the tumour progression. This scarcity of good progressive biomarkers has led us to search for better options. SERPINA3 and SPP1 were investigated as potential dual biomarkers reflecting tumour microenvironment and enabling assessment of progression. In silico analysis was conducted, where correlation analysis was performed to evaluate the cell-type specificity of SERPINA3 in astrocytes and SPP1 in microglial cells, with comparisons across other neural populations in both low-grade glioma and glioblastoma. Pan-cancer expression analysis was conducted to determine whether these biomarkers remain significantly elevated in glioma relative to other malignancies, including hepatocellular carcinoma, given their hepatic origin. Alzheimers disease datasets were analysed to verify the relevance in neurodegenerative diseases. The in-silico analysis revealed that SERPINA3 and SPP1 show astrocytic and microglial specificity, respectively, and exhibit their highest expression levels in glioma across cancers. Co-expression analysis further identified enrichment of immunoregulatory pathways alongside upregulated oxidative stress-associated markers, highlighting the functional relevance of these biomarkers within the glioma microenvironment.

neuroscience↗

bioRxiv2025

Parallel but distinct adaptive routes in the budding and fission yeasts after 10,000 generations of experimental evolution

Quantitative genetics approaches designed to understand the evolution of traits have helped improve our understanding of the genetic basis of adaptation. However, they often overlook crucial aspects of adaptation, including the long-term temporal evolutionary dynamics, the predictability of evolutionary outcomes, the influence of past evolution on future evolutionary trajectories (contingency), and the diversity of molecular mechanisms underlying adaptation. Experimental evolution has been a useful tool for answering these questions, but extracting fundamental principles and predictive features of evolutionary outcomes from these datasets remains challenging due to the large number of covariates and confounding effects, such as differences in experimental setup, species lifestyle, gene content, and evolution rate. Here, we sought to circumvent these challenges by comparing distant yeast species that share several evolutionary features but differ mainly in evolutionary history and genome architecture, i.e. Saccharomyces cerevisiae and Schizosaccharomyces pombe. Thus, we evolved 10 populations of the fission yeast for 10,000 generations in the same conditions as a pre-existing budding yeast dataset (i.e. high-sugar media and hypoxic conditions), allowing us to observe repeatable evolutionary outcomes within species but diverse molecular mechanisms and targets of adaptation across species. The most frequent adapting route in these conditions involved upregulating fermentation genes and downregulating the glycolysis gene pyk1, which has not previously been observed in S. cerevisiae evolved populations or in wild Kluyveromyces lactis, but similar evolutionary paths have been observed in Schizosaccharomyces japonicus and in clinically relevant populations, such as some cancer cells. This suggests that parallelism is pervasive in the tree of life and that mechanisms of adaptation can be shared among closely related or distant species. Despite similar gene content and identical environments, recurrent adaptation across S. pombe populations involved different genes than in S. cerevisiae and was mostly detectable at the transcriptomic level. This suggests that trans-regulatory effects may play an important role in adaptation on short evolutionary timescales and that differences in evolutionary outcomes between these species may be attributed to contingency.

evolutionary biology↗

bioRxiv2020

Phenotypic and molecular evolution across 10,000 generations in laboratory budding yeast populations

Laboratory experimental evolution provides a window into the details of the evolutionary process. To investigate the consequences of long-term adaptation, we evolved 205 S. cerevisiae populations (124 haploid and 81 diploid) for [~]10,000 generations in three environments. We measured the dynamics of fitness changes over time, finding repeatable patterns of declining adaptability. Sequencing revealed that this phenotypic adaptation is coupled with a steady accumulation of mutations, widespread genetic parallelism, and historical contingency. In contrast to long-term evolution in E. coli, we do not observe long-term coexistence or populations with highly elevated mutation rates. We find that evolution in diploid populations involves both fixation of heterozygous mutations and frequent loss-of-heterozygosity events. Together, these results help distinguish aspects of evolutionary dynamics that are likely to be general features of adaptation across many systems from those that are specific to individual organisms and environmental conditions.

evolutionary biology↗