Antimicrobial Resistance Surveillance Methods in Bangladesh: Present and Way Forward.

The Institute of Epidemiology, Disease Control and Research (IEDCR) conducts active, case-based national antimicrobial resistance (AMR) surveillance in Bangladesh. The Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project accessed aggregated retrospective data from non-IEDCR study sites and 9 IEDCR sites to understand the pattern and extent of AMR and to use analyzed data to guide ongoing and future national AMR surveillance in both public and private laboratories. Record-keeping practices, data completeness, quality control, and antimicrobial susceptibility test practices were investigated in all laboratories participating in case-based IEDCR surveillance and laboratory-based CAPTURA sites. All 9 IEDCR laboratories recorded detailed case-based data (n = 16 816) in electronic format for a priority subset of processed laboratory samples. In contrast, most CAPTURA sites (n = 18/33 [54.5%]) used handwritten registers to store data. The CAPTURA sites were characterized by fewer recorded variables (such as patient demographics, clinical history, and laboratory findings) with 1 020 197 individual data, less integration of patient records with the laboratory information system, and nonuniform practice of data recording; however, data were collected from all available clinical samples. The analyses conducted on AMR data collected by IEDCR and CAPTURA in Bangladesh provide current data collection status and highlight opportunities to improve ongoing data collection to strengthen current AMR surveillance system initiatives. We recommend a tailored approach to conduct AMR surveillance in high-burden, resource-limited settings.

Molecular characterization of SARS-CoV-2 from Bangladesh: implications in genetic diversity, possible origin of the virus, and functional significance of the mutations.

In a try to understand the pathogenesis, evolution and epidemiology of the SARS-CoV-2 virus, scientists from all over the world are tracking its genomic changes in real-time. Genomic studies can be helpful in understanding the disease dynamics. We have downloaded 324 complete and near complete SARS-CoV-2 genomes submitted in GISAID database from Bangladesh which were isolated between 30 March to 7 September, 2020. We then compared these genomes with Wuhan reference sequence and found 4160 mutation events including 2253 missense single nucleotide variations, 38 deletions and 10 insertions. The C>T nucleotide change was most prevalent (41% of all mutations) possibly due to selective mutation pressure to reduce CpG sites to evade CpG targeted host immune response. The most frequent mutation that occurred in 98% isolates was 3037C>T which is a synonymous change that usually accompanied 3 other mutations that include 241C>T, 14408C>T (P323L in RdRp) and 23403A>G (D614G in spike protein). The P323L was reported to increase mutation rate and D614G is associated with increased viral replication and currently most prevalent variant circulating all over the world. We identified multiple missense mutations in B-cell and T-cell predicted epitope regions and/or PCR target regions (including R203K and G204R that occurred in 86% of the isolates) that may impact immunogenicity and/or RT-PCR based diagnosis. Our analysis revealed 5 large deletion events in ORF7a and ORF8 gene products that may be associated with less severity of the disease and increased viral clearance. Our phylogeny analysis identified most of the isolates belonged to the Nextstrain clade 20B (86%) and GISAID clade GR (88%). Most of our isolates shared common ancestors either directly with European countries or jointly with middle eastern countries as well as Australia and India. Interestingly, the 19B clade (GISAID S clade) was unique to Chittagong, which was originally prevalent in China. This reveals possible multiple introductions of the virus in Bangladesh via different routes. Hence, more genome sequencing and analysis with related clinical data is needed to interpret functional significance and better predict the disease dynamics that may be helpful for policy makers to control the COVID-19 pandemic.

Circulating strains of Mycobacterium tuberculosis: 24 loci MIRU-VNTR analysis in Bangladesh.

Bangladesh is among the high burden countries for tuberculosis (TB) and multidrug resistant TB (MDR-TB). As the genetic diversity and distinct phylogeographic distribution of Mycobacterium tuberculosis are responsible for regional differences in drug resistance, this cross sectional study was conducted to identify the circulating M. tuberculosis strains belonging to different lineages among pulmonary tuberculosis and, to investigate the contribution of distinct M. tuberculosis lineages to rifampicin resistant (RR) and rifampicin sensitive (RS) TB. A total of 40 RR and 20 RS isolates were enrolled in this study, all of which confirmed as M. tuberculosis by MPT 64 antigen detection. Furthermore, all isolates were genotyped by 24 loci Mycobacterial Interspersed Repetitive Units-Variable Number of Tandem Repeats (MIRU-VNTR), thus comprising the first study to employ this approach in Bangladesh. Beijing was the predominant lineage (26.8%) followed by EAI (23.2%), Delhi/CAS (16.1%), H37Rv (8.9%), Haarlem (7.1%), LAM (5.4%), Cameroon (3.6%) and a NEW-1 (1.8%). Four (7.1%) isolates remained as unidentified. Beijing strains were the significantly predominant (36.8%; p = 0.0135) among the RR isolates in comparison with other strains whereas EAI was the predominant (38.8%) lineage among RS isolates. Also, approximately 13% RR isolates showed genotypic resistance against fluoroquinolones by LPA and, hence, classed as pre-XDR TB albeit no specific lineage was found associated with these latter strains. A low transmission rate (10.5%) and high genetic diversity was detected in this setting with all the clustered strains herein identified belonging to the Beijing lineage. This study highlights 24 loci MIRU-VNTR analysis as a powerful tool for genotyping of Mycobacterium tuberculosis in this setting as it shows a high discriminatory index (0.81).