Biology subjects

Islam, T. N.

Publications and source records attributed to Islam, T. N..

3 recordsLinked to original sources

bioRxiv2024

Optimization of citric acid production from sugarcane molasses using Aspergillus niger by submerged Fermentation

The potentiality of citric acid on economy is high because of its multi-purpose uses, particularly in the food and pharmaceutical industries. Bangladesh spent more than million US dollars to import citric acid mostly from India and China. Its consumption is increasing 3.5-4%, annually, indicating the need for better manufacturing alternatives. Globally, citric acid is primarily produced through microbial fermentation with Aspergillus niger. To support the massive scale of production of citrate, the manufacturing process must be eco-friendly which should be inexpensive and available raw materials for maintaining high yielding in a cost-effective manner. In Bangladesh prospective, the current study has undertaken to optimize citric acid production using one of the most abundant raw materials sugarcane molasses. Moreover, the aim of this study was to determine the optimum conditions to produce citric acid from sugarcane molasses using Aspergillus niger (F-81) by submerged fermentation. The amount of citric acid production was determined by Marier-Boulet colorimetric method. The optimization data suggested that 10% substrate (from processed cane molasses), 4% inoculum size of A. niger, and initial pH 6.0 allowed to produce around 25.8 g/L citric acid. Further study is warranted to assess the feasibility of citrate production in an industrial level as well as improvement of microbial strains is needed to further enhance citric acid production.

microbiology↗

bioRxiv2024

Prediction of protein-carbohydrate binding sites from protein primary sequence

BackgroundA protein is a large complex macromolecule that has a crucial role in performing most of the work in cells and tissues. It is made up of one or more long chains of amino acid residues. Another important biomolecule, after DNA and protein, is carbohydrate. Carbohydrates interact with proteins to run various biological processes. Several biochemical experiments exist to learn the protein-carbohydrate interactions, but they are expensive, time-consuming, and challenging. Therefore, developing computational techniques for effectively predicting protein-carbohydrate binding interactions from protein primary sequence has given rise to a prominent new field of research. ResultIn this study, we propose StackCBEmbed, an ensemble machine learning model to effectively classify protein-carbohydrate binding interactions at residue level. StackCBEmbed combines traditional sequence-based features along with features derived from a pre-trained transformer-based protein language model. To the best of our knowledge, ours is the first attempt to apply protein language model in predicting protein-carbohydrate binding interactions. StackCBEmbed achieved sensitivity and balanced accuracy scores of 0.730, 0.776 and 0.666, 0.742 in two separate independent test sets. This performance is superior compared to the earlier prediction models benchmarked in the same datasets. ConclusionWe thus hope that StackCBEmbed will discover novel protein-carbohydrate interactions and help advance the related fields of research. StackCBEmbed is freely available as Python scripts at https://github.com/nafiislam/StackCBEmbed.

bioinformatics↗

bioRxiv2023

Chromium/cadmium plays a pivotal role to emerge amoxicillin resistant Staphylococcus aureus

RationaleThe rapid emergence of resistant bacteria is occurring worldwide, endangering the efficacy of antimicrobials. Apart from horizontal gene transfer and plasmid mediated antimicrobial resistance (AMR) acquisition, co-exposure of heavy metals and antibiotics cause to emerge AMR Enterobacteriaceae. Heavy metals and antimicrobials co-exist in many environmental settings. We hypothesized that heavy metals and lower dose of antibiotic co-exposure may alter levels of antimicrobial susceptibility and facilitate to emerge AMR bacteria. MethodsThe growth kinetics of antimicrobial susceptible Staphylococcus aureus ST80 was carried out in the presence of chromium/cadmium salt and a lower dose of antibiotics. Subsequently, the antimicrobials susceptibility patterns of heavy metals pre-exposed for 48 hours Staphylococcus aureus ST 80 was determined by Kirby-Bauer disc diffusion method. ResultsThe antimicrobial susceptibility profile revealed that the zone of inhibition (ZOI) for ampicillin, amoxicillin, ciprofloxacin and doxycycline significantly decreased in chromium pre-exposed Staphylococcus compared to unexposed bacteria. However, cadmium pre-exposed bacteria only showed significant decreased ZOI for amoxicillin. Moreover, the MIC of amoxicillin was increased by 8-fold in chromium and 32-fold in cadmium with a low-dose of amoxicillin co-exposed bacteria. Besides, the RT-qPCR data demonstrated that chromium and a low-dose of amoxicillin pre-exposed significantly increased the mRNA expression of femX (25-fold), mepA (19-fold) and norA (17-fold) in S. aureus. In essence, minimum levels of chromium/cadmium and a MIC of amoxicillin exposure induced efflux pumps, which might responsible to emerge amoxicillin resistant S. aureus.

microbiology↗