Abstracts

Research Articles 

Challenges for activating undergraduate research: a summary from the 2021 American Society for Microbiology Conference for Undergraduate Educators

Based on a growing understanding of the many benefits of undergraduate research, advocacy for undergraduate research experiences has increased, with an emphasis on implementing course-based undergraduate research experiences (CUREs). To understand existing efforts to promote undergraduate research as well as challenges to implementation on higher education campuses, we hosted a session about undergraduate research at the 2021 American Society for Microbiology Conference for Undergraduate Educators. Session participants were surveyed about their experiences with undergraduate research on their home campuses, and we then conducted additional research on the undergraduate research offerings at the participants’ home institutions. Survey responses and the discussion group identified many challenges to impactful undergraduate research facilitation. Several overarching themes emerged across survey responses and breakout room discourse, including funding, mentor recruitment, early skill development, diversity, equity, and inclusion (DEI) and identifying and connecting with students. In this perspective, we elaborate on this discourse to inspire and assist those seeking to foster undergraduate research in the field of microbiology and beyond.

Finding the Connections: A Scoping Review of Epistemic Network Analysis in Science Education

As science education scholars learn more about how people learn, instructors have begun to shift from teaching science as lists of facts and asking students to synthesize ideas into cognitive models or networks. Therefore, the methodologies we use to understand students’ and instructors’ ways of knowing need to capture this complexity. Within education, one methodology that has emerged to capture this complexity is epistemic network analysis (ENA). ENA is a potentially useful tool for understanding connections between people’s ideas and cognitive constructs. Because of its mixed methods approach, ENA is able to provide the depth of qualitative analysis and allow synthesis and comparison across large quantities of data. In this review, we present findings from a scoping literature review of ENA in science education. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework, we extracted data from 19 articles. This data consisted of both context-related variables (i.e., disciplinary field) and application-based variables (i.e., theoretical frameworks, research design). Finally, we discuss the findings from this review and their implications for science education.

Identification and antibiotic pattern analysis of bacillary dysentery-causing bacteria isolated from stool samples of infected patients

Bacillary dysentery is a type of dysentery and a severe form of shigellosis. This dysentery is usually restricted to Shigella infection, but Salmonella enterica and enteroinvasive Escherichia coli strains are also known as this infection’s causative agents. The emergence of drug-resistant, bacillary dysentery-causing pathogens is a global burden, especially for developing countries with poor hygienic environments. This study aimed to isolate, identify, and determine the drug-resistant pattern of bacillary dysentery-causing pathogens from the stool samples of the Kushtia region in Bangladesh. Hence, biochemical tests, serotyping, molecular identification, and antibiotic profiling were performed to characterize the pathogens. Among one hundred fifty (150) stool samples, 18 enteric bacterial pathogens were isolated and identified, where 12 were Shigella strains, 5 were S. enterica sub spp. enterica strains and one was the E.coli strain. Among 12 Shigella isolates, 8 were Shigella flexneri 2a serotypes, and 4 were Shigella sonnei Phage-II serotypes. Except for three Salmonella strains, all isolated strains were drug-resistant (83%), whereas 50% were multidrug-resistant (MDR), an alarming issue for public health. In antibiotic-wise analysis, the isolated pathogens showed the highest resistance against nalidixic acid (77.78%), followed by tetracycline (38.89%), kanamycin (38.89%), amoxicillin (27.78%), streptomycin (27.78%), cefepime (22.22%), ceftriaxone (22.22%), ampicillin (16.67%), ciprofloxacin (16.67%), and chloramphenicol (16.67%). The existence of MDR organisms that cause bacillary dysentery in the Kushtia area would warn the public to be more health conscious, and physicians would administer medications cautiously. The gradual growth of MDR pathogenic microorganisms needs immediate attention, and the discovery of effective medications must take precedence.

Mycoremediation of reactive red HE7B dye by Aspergillus salinarus isolated from textile effluents

Reactive dyes are widely utilized in the textile industry due to their advantageous properties of vivid color, water-fastness, and simple application procedures with minimal energy usage. The toxicity of most azo dyes is a significant environmental concern, as effluents from dye processing and manufacturing sectors are known to be carcinogenic and mutagenic to numerous species. These issues are more grievous in Bangladesh, one of the largest exporters of apparel. This study aimed to isolate and identify potential fungal strains from textile effluent that are capable of degrading Reactive Red HE7B dye (a sulphonated reactive azo dye), a widely used dye in local thread dyeing industries. Dye degradation assay was performed in potato dextrose broth supplemented with 50 mg/l Reactive Red HE7B and the degradation rate was measured by a UV spectrophotometer. DNA extraction, quantification, PCR, internal transcribed spacer (ITS) sequencing, and phylogenetic analysis were performed to identify the selected fungi. Among the isolates, the three best performing strains TEF -3, TEF -4, and TEF -5 showed 97.41%, 93.12%, and 82.89% dye degrading efficacy after 96 h of incubation, respectively. All three strains, TEF-3, TEF-4, and TEF-5 showed similarity with Aspergillus salinarus (accession no. NR_157473.1) and the similarity percentages were 97.02, 96.95, and 95.28 respectively. Interestingly, this study probably the very first indication of textile dye degradation by Aspergillus salinarus strains. Thus, these fungal strains possess the prospectiveness to be utilized in the textile wastewater treatment plants, since the isolates demonstrated the substantial capacity (>80%) to degrade Reactive Red dye after 96 h of incubation.

Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Comparative proteomic analysis to annotate the structural and functional association of the hypothetical proteins of S. maltophilia k279a and predict potential T and B cell targets for vaccination

Stenotrophomonas maltophilia is a multidrug-resistant bacterium with no precise clinical treatment. This bacterium can be a vital cause for death and different organ failures in immune-compromised, immune-competent, and long-time hospitalized patients. Extensive quorum sensing capability has become a challenge to develop new drugs against this pathogen. Moreover, the organism possesses about 789 proteins which function, structure, and pathogenesis remain obscured. In this piece of work, we tried to enlighten the aforementioned sectors using highly reliable bioinformatics tools validated by the scientific community. At first, the whole proteome sequence of the organism was retrieved and stored. Then we separated the hypothetical proteins and searched for the conserved domain with a high confidence level and multi-server validation, which resulted in 24 such proteins. Furthermore, all of their physical and chemical characterizations were performed, such as theoretical isoelectric point, molecular weight, GRAVY value, and many more. Besides, the subcellular localization, protein-protein interactions, functional motifs, 3D structures, antigenicity, and virulence factors were also evaluated. As an extension of this work, ’RTFAMSSER’ and ’PAAPQPSAS’ were predicted as potential T and B cell epitopes, respectively. We hope our findings will help in better understating the pathogenesis and smoothen the way to the cure.

Computational formulation and immune dynamics of a multi-peptide vaccine candidate against Crimean-Congo hemorrhagic fever virus

The sole objective of this research is to devise an epitope-based vaccine candidate as prophylaxis for the Crimean-Congo hemorrhagic fever virus (CCHFV) using the knowledge of immunoinformatics and structural biology. Importantly, CCHFV outbreaks have increased in several countries resulting in increased mortality up to 40% due to the lack of prospective medication and an efficient vaccine. In this study, we have used several immunoinformatic tools and servers to anticipate potent B-cell and T-cell epitopes from the CCHFV glycoprotein with the highest antigenicity. After a comprehensive evaluation, a vaccine candidate was designed using 6 CD8+, 3 CD4+, and 7 B-cell epitopes with appropriate linkers. To enhance the vaccine's efficiency, we added Mycobacterium tuberculosis lipoprotein LprG (Rv1411c) to the vaccine as an adjuvant. The final construct was composed of a total of 468 amino acid residues. The epitope included in the construct showed 98% worldwide population coverage. Importantly, the construct appeared as antigenic, immunogenic, soluble, and non-allergenic in nature. To explore further, we modelled the three-dimensional (3D) structure of the constructed vaccine. Our chimeric vaccine showed stable and strong interactions for toll-like receptor 2 (TLR2) found on the cell surface. Moreover, the dynamics simulation of immune response showed elevated levels of cellular immune activity and faster clearance of antigen from the body upon repetitive exposure. Finally, the optimized codon (CAI≈1) ensured the marked translation efficiency of the vaccine protein in E. coli strain K12 bacterium followed by the insertion of construct DNA into the cloning vector pET28a (+). We believe that the designed vaccine chimera could be useful in vaccine development to fight CCHFV outbreaks.

Inhibition of biofilm formation, quorum sensing and other virulence factors in Pseudomonas aeruginosa by polyphenols of Gynura procumbens leaves

Quorum sensing (QS) enables virulence factors in bacteria for biofilm formation and pathogenic invasion. Therefore, quorum quenching (QQ), disruption of QS circuit, becomes an alternative antimicrobial therapy. In this study, leaf extract of Gynura procumbens (GP) was used to inhibit biofilm and virulent factors in Pseudomonas aeruginosa. The extract inhibited the biofilm production (p ≤ 0.05) in P. aeruginosa strains MZ2F and MZ4A. The minimum biofilm eradication concentration (MBEC) was recorded at 250 and 500 μg/ml while total activity was found at 288 and 144 ml/g, respectively. Moreover, a significant reduction of virulence factors (p ≤ 0.05) at sub-MBEC without affecting the growth implies the QQ action of the extract. The bioactive fractions were rich in polyphenols and tentatively identified as quercetin and myricetin (Rf=0.53-0.60). Furthermore, we employed computational methods to validate our findings and their interactions with QS receptors (LasR and RhlR). Interestingly, docking studies have also shown that quercetin and myricetin are the promising anti-QS agents out of 31 GP compounds. Notably, their binding affinity ranged between −9.77 and −10.52 kcal/mol for both QS receptors, with controls ranging from −5.40 to −8.97 kcal/mol. Besides, ΔG of quercetin and myricetin with LasR was −71.56 and −74.88 kcal/mol, respectively. Moreover, compounds were suitable drug candidates with stable binding interactions. Therefore, the anti-QS activity of GP leaves and the identified polyphenols can be used in developing QQ-based therapeutics.

Major Nutritional Constituents and Genetic Diversity Analysis of Different Strains of Oyster Mushrooms

Oyster mushroom is the second runner-up among commercially produced mushrooms due to its delicious taste, higher nutritional and medicinal properties. The objectives of this study were to determine the nutritional variation through the analysis of obtained nutritional values and to assess the genetic diversity through RAPD marker of five different strains of oyster mushrooms namely Pleurotus cystidiosus (strain: pcys2); Pleurotus djamor (pop1); Pleurotus ostreatus (ws); Pleurotus ostreatus (po3) and Pleurotus geesteranus (pg4). The strains showed variations in moisture, protein, fiber, lipid, ash and carbohydrate content ranged from 86.10-87.33%; 17.8-24.13 gm/100gm; 18.16- 25.46 gm/100gm; 3.16-5.16 gm/100gm; 9.16-11.46 gm/100gm; and 35.4-45.33 gm/100gm respectively. In case of genetic diversity, the segregation of five strains of oyster mushrooms were grouped through un-weighted pair group method of arithmetic means average (UPGMA), where strains were grouped into two main clusters and the generated linkage distance was 48. The strains pop1 and po3 were aligned in cluster two (C2) due to their genetic similarity but showed dissimilarities with other strains. Though the strains pcys2, ws, and pg4 were aligned in the same cluster (C1), the strain ws was aligned in a different sub-cluster due to its few dissimilarities with the other two strains. The variation of nutritional values and genetic diversities among the mushroom strains indicates nutritional and genetic variabilities. The findings of current study indicate that, though these mushrooms were genetically dissimilar, all strains were nutritious with high protein and fiber contents with low fat. However, mushroom breeder can consider strain po3 for high protein content, strain ws for high fiber content and strain pop1 for low fat content.

Exploring Lassa Virus Proteome to Design a Multi‑epitope Vaccine Through Immunoinformatics and Immune Simulation Analyses

Lassa virus (LASV) is responsible for a type of acute viral haemorrhagic fever referred to as Lassa fever. Lack of adequate treatment and preventive measures against LASV resulted in a high mortality rate in its endemic regions. In this study, a multi-epitope vaccine was designed using immunoinformatics as a prophylactic agent against the virus. Following a rigorous assessment, the vaccine was built using T-cell (NCTL = 8 and NHTL = 6) and B-cell (NLBL = 4) epitopes from each LASV-derived protein in addition with suitable linkers and adjuvant. The physicochemistry, immunogenic potency and safeness of the designed vaccine (~ 68 kDa) were assessed. In addition, chosen CTL and HTL epitopes of our vaccine showed 97.37% worldwide population coverage. Besides, disulphide engineering also improved the stability of the chimeric vaccine. Molecular docking of our vaccine protein with toll-like receptor 2 (TLR2) showed binding efficiency followed by dynamics simulation for stable interaction. Furthermore, higher levels of cell-mediated immunity and rapid antigen clearance were suggested by immune simulation and repeated-exposure simulation, respectively. Finally, the optimized codons were used in in silico cloning to ensure higher expression within E. coli K12 bacterium. With further assessment both in vitro and in Vivo, we believe that our proposed peptide-vaccine would be potential immunogen against Lassa fever.

Proteome-wide screening for designing a multiepitope vaccine against emerging pathogen Elizabethkingia anophelis using immunoinformatic approaches

Elizabethkingia anophelis is an emerging human pathogen causing neonatal meningitis, catheter-associated infections and nosocomial outbreaks with high mortality rates. Besides, they are resistant to most antibiotics used in empirical therapy. In this study, therefore, we used immunoinformatic approaches to design a prophylactic peptide vaccine against E. anophelis as an alternative preventive measure. Initially, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were predicted from the highest antigenic protein. The CTL and HTL epitopes together had a population coverage of 99.97% around the world. Eventually, six CTL, seven HTL, and two LBL epitopes were selected and used to construct a multi-epitope vaccine. The vaccine protein was found to be highly immunogenic, non-allergenic, and non-toxic. Codon adaptation and in silico cloning were performed to ensure better expression within E. coli K12 host system. The stability of the vaccine structure was also improved by disulphide bridging. In addition, molecular docking and dynamics simulation revealed strong and stable binding affinity between the vaccine and toll-like receptor 4 (TLR4) molecule. The immune simulation showed higher levels of T-cell and B-cell activities which was in coherence with actual immune response. Repeated exposure simulation resulted in higher clonal selection and faster antigen clearance. Nevertheless, experimental validation is required to ensure the immunogenic potency and safety of this vaccine to control E. anophelis infection in the future.

A comprehensive screening of the whole proteome of hantavirus and designing a multi-epitope subunit vaccine for cross-protection against hantavirus: Structural vaccinology and immunoinformatics study

Hantaviruses are an emerging zoonotic group of rodent-borne viruses that are having serious implications on global public health due to the increase in outbreaks. Since there is no permanent cure, there is increasing interest in developing a vaccine against the hantavirus. This research aimed to design a robust cross-protective subunit vaccine using a novel immunoinformatics approach. After careful evaluation, the best predicted cytotoxic & helper T-cell and B-cell epitopes from nucleocapsid proteins, glycoproteins, RdRp proteins, and non-structural proteins were considered as potential vaccine candidates. Among the four generated vaccine models with different adjuvant, the model with toll-like receptor-4 (TLR-4) agonist adjuvant was selected because of its high antigenicity, non-allergenicity, and structural quality. The selected model was 654 amino acids long and had a molecular weight of 70.5 kDa, which characterizes the construct as a good antigenic vaccine candidate. The prediction of the conformational B-lymphocyte (CBL) epitope secured its ability to induce the humoral response. Thereafter, disulfide engineering improved vaccine stability. Afterwards, the molecular docking confirmed a good binding affinity of −1292 kj/mol with considered immune receptor TLR-4 and the dynamics simulation showed high stability of the vaccine-receptor complex. Later, the in silico cloning confirmed the better expression of the constructed vaccine protein in E. coli K12. Finally, in in silico immune simulation, significantly high levels of immunoglobulin M (IgM), immunoglobulin G1 (IgG1), cytotoxic & helper T lymphocyte (CTL & HTL) populations, and numerous cytokines such as interferon-γ (IFN-γ), interleukin-2 (IL-2) etc. were found as coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Nonetheless, experimental validation can demonstrate the safety and cross-protective ability of the proposed vaccine to fight against hantavirus infection.

Energy-optimized pharmacophore coupled virtual screening in the discovery of quorum sensing inhibitors of LasR protein of Pseudomonas aeruginosa

Pseudomonas aeruginosa is an emerging opportunistic pathogen responsible for cystic fibrosis and nosocomial infections. In addition, empirical treatments are become inefficient due to their multipleantibiotic resistance and extensive colonizing ability. Quorum sensing (QS) plays a vital role in the regulation of virulence factors in P. aeruginosa. Therefore, attenuation of virulence by QS inhibition could be an alternative and effective approach to control the infections. In this study, we sought to discover new QS inhibitors (QSIs) against LasR receptor in P. aeruginosa using chemoinformatics. Initially, a structure-based high-throughput virtual screening was performed using the LasR active site that identified 61404 relevant molecules. The e-pharmacophore (ADAHH) screening of these molecules rendered 72 QSI candidates. In standard-precision docking, only 7 compounds were found as potential QSIs based on their higher binding affinity to LasR receptor (7.53 to 10.32 kcal/mol compared to 7.43 kcal/mol of native ligand). The ADMET properties of these compounds were suitable to be QSIs. Later, extra-precision docking and binding energy calculation suggested ZINC19765885 and ZINC72387263 as the most promising QSIs. The dynamic simulation of the docked complexes showed stable binding affinity and molecular interactions. The current study suggested that these two compounds could be used in P. aeruginosa QS inhibition to combat bacterial infections.

 Antibiograms of Multidrug-resistant Acinetobacter baumannii Isolated from Specimens at Kushtia Medical College Hospital [Bachelor's Micro-thesis]

Acinetobacter baumannii is an opportunistic, hospital dwelling pathogen which is responsible for hospital-acquired infections like Ventilator-associated pneumonia (VAP), several respiratory and urinary tract infections, meningitis, wound sepsis and numerous skin/soft tissue infections (SSTIs). The emergence of this notorious bacteria is profoundly observed by recent outbreaks throughout the world. The dominance of this pathogen thrives over the healthcare units, because of its ability to resist every existing first-line antibiotics, reminding the fear of the preantibiotic era to the world. The aim of this study was to isolate and identify A. baumannii from clinical samples and to determine their antimicrobial resistance pattern to commonly prescribed drugs to find out multidrug-resistant A. baumannii (MDRAB). Four different samples were collected from Kushtia Medical College Hospital. A. baumannii was isolated and identified based on their growth, physiological, and biochemical characteristics. Their antibiograms were studied through standard disk diffusion method, and antibiotic susceptibility patterns were interpreted. Ceftriaxone, ciprofloxacin, erythromycin, imipenem and colistin were used to evaluate the sensitivity of the isolates. Out of four specimens, the pathogen was recovered from hospital drain water, hospital dust and urine sample. Though the isolates showed similar growth and physiological characteristics along with similar biochemical profiles, they differ considerably in their sensitivity against several antibiotics. The least resistance showing antibiotic was colistin (22%) and then imipenem (33%). Aside from isolate DW04, HD19, HD20, HD24, all isolates found multidrug-resistant (resistant to ≥ 3 antibiotics group). The recovery of MDRAB, including imipenem-resistant A. baumannii from different clinical specimens, and their antibiotic resistance pattern hint emergence of a formidable pathogen of nosocomial origin. The findings of the study seek up-gradation of current patient maintenance practices in healthcare units of our country to limit the prevalence of antibiotic-resistant A. baumannii.

Review Articles

Community-acquired pneumonia: aetiology, antibiotic resistance and prospects of phage therapy

Bacteria are the most common aetiological agents of community-acquired pneumonia (CAP) and use a variety of mechanisms to evade the host immune system. With the emerging antibiotic resistance, CAP-causing bacteria have now become resistant to most antibiotics. Consequently, significant morbimortality is attributed to CAP despite their varying rates depending on the clinical setting in which the patients being treated. Therefore, there is a pressing need for a safe and effective alternative or supplement to conventional antibiotics. Bacteriophages could be a ray of hope as they are specific in killing their host bacteria. Several bacteriophages had been identified that can efficiently parasitize bacteria related to CAP infection and have shown a promising protective effect. Thus, bacteriophages have shown immense possibilities against CAP inflicted by multidrug-resistant bacteria. This review provides an overview of common antibiotic-resistant CAP bacteria with a comprehensive summarization of the promising bacteriophage candidates for prospective phage therapy.

COVID-19: The catastrophe of our time

The most discussed topic in today's world is COVID-19, an acute respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because of its contagious transmission pattern, and morbimortality. The virus was originated by bats and in December 2019, first spread to humans by unknown intermediate species in Wuhan, China. The dramatic acceleration of the occurrence and death toll of COVID-19 with no potential medicine and vaccine are enough to explain its severity. This review summarizes multidisciplinary aspects of COVID-19, including origin, epidemiology, symptoms, transmission, pathogenicity, impact on world economy and advances in the use of modern diagnostic procedures and methods. Further, we analyzed extensively for various therapeutic strategies, potential drug options with prospective vaccine candidates and challenges along the way. All data were accumulated through extensive study of recent peer-reviewed publications and authentic reports until June 7, 2020. Collectively, this review would help to shed light on different dimensions of this ongoing pandemic.

Research Projects 

Mutiepitope Vaccine Design Project

During my junior year, I embarked on my first research project in computational biology, working alongside my academic predecessors, Utpal Kumar Adhikari and Zulkar Nain. Together, we proposed epitope-based vaccines against a range of infectious bacteria and viruses, including Lassa virus, Crimean-Congo haemorrhagic fever (CCHFV), Hantavirus, and Elizabethkingia anophelis. Through this project, I developed a diverse skill set encompassing proteomic data analysis, allergenicity and antigenicity assessment, physiochemical properties evaluation, epitope and MHC allele prediction, immune simulation, and other immunoinformatic attributes. This research experience introduced me to the complexities of vaccine development, which has since fascinated me.

Quorum Sensing Inhibitor (QSI) Project

During my final year of undergraduate studies, I participated in a microbiology research project where we identified biofilm-forming multidrug-resistant Pseudomonas aeruginosa from clinical and commensal sources. As quorum sensing (QS) controls biofilm and related traits, we investigated the anti-QS potency of Gynura procumbens leaf extract. Our positive results led us to investigate the underlying mechanism and to tentatively characterize the responsible phytochemicals as flavonoids and phenols. Through this project, I gained experience in various techniques such as biofilm and antibiofilm assays, phytochemical tests, and column and thin-layer chromatography. Concurrently, we conducted another project searching for a suitable inhibitor against the LasR receptor, the principal QS regulon, where we identified 7 potential compounds out of 100,000. This work allowed me to develop comprehensive knowledge and skills in molecular docking and dynamics simulation. The study was recently published in the Journal of Biomolecular Structure and Dynamics.

Mycoremmediation of Textile Effluants

Under the supervision of Dr. Sudhangshu Kumar Biswas, our research focused on the detrimental effects of Bangladesh's apparel industry on water health caused by the mass disposal of dyes. Specifically, we investigated the ability of Aspergillus fumigatus to degrade reactive red dye. During the project, I gained invaluable experience in dye-degradation assay techniques, as well as photo-electric-colorimeter and PCR techniques. Notably, out of the six isolated fungal strains, A. fumigatus TEF-3 demonstrated the highest potency in degrading the RR dye, with a 97.41% degradation rate at a concentration of 50 mg/l after 96 hours of incubation. This discovery suggests the potential use of A. fumigatus TEF-3 in textile wastewater treatment plants.

Impact of COVID-19 on comorbidities

Under the supervision of prominent data scientist Dr Mohammad Ali Moni, I have worked on the transcriptomics analysis of COVID-19 to understand its impact on various comorbidities, including, diabetes mellitus (DM), lung cancer (LC), myocardial infarction (MI), and hypertension (HT). Notably, COVID-19 shared three upregulated genes (i.e., MX2, IRF7, and ADAM8) with DM and LC. Conversely, the downregulation of two genes (i.e., PPARGC1A and METTL7A) was found in COVID-19 and LC. In addition, the majority of their shared pathways were related to inflammatory responses. Furthermore, prognostic analysis suggests concomitant COVID-19 may result in poor outcomes for LC patients. I adapted skills like microarray data analysis, cancer survival, comorbidity analysis, and protein-protein interaction.