Biology subjects

Abebe, T.

Publications and source records attributed to Abebe, T..

4 recordsLinked to original sources

bioRxiv2020

Population structure and transmission of Mycobacterium bovis in Ethiopia

Bovine tuberculosis (bTB) is endemic in cattle in Ethiopia, a country that hosts the largest national cattle herd in Africa. The intensive dairy sector, most of which is peri-urban, has the highest prevalence of disease. Previous studies in Ethiopia have demonstrated that the main cause is Mycobacterium bovis (M. bovis), which has been investigated using conventional molecular tools including deletion typing, spoligotyping and Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR). Here we use whole genome sequencing (WGS) to examine the population structure of M. bovis in Ethiopia. A total of 134 M. bovis isolates were sequenced including 128 genomes from 85 mainly dairy cattle and six genomes isolated from humans, originating from 12 study sites across Ethiopia. These genomes provided a good representation of the previously described population structure of M. bovis, based on spoligotyping and demonstrated that the population is dominated by the clonal complexes African 2 (Af2) and European 3 (Eu3). A range of within-host diversity was observed amongst the isolates and evidence was found for both short- and long-distance transmission. Detailed analysis of available genomes from the Eu3 clonal complex combined with previously published genomes revealed two distinct introductions of this clonal complex into Ethiopia between 1950 and 1987, likely from Europe. This work is important to help better understand bTB transmission in cattle in Ethiopia and can potentially inform national strategies for bTB control in Ethiopia and beyond.

genomics↗

bioRxiv2020

Sero-prevalence of anti-SARS-CoV-2 Antibodies in Addis Ababa, Ethiopia

BackgroundAnti-SARS-CoV-2 antibody tests are being increasingly used for sero-epidemiological purposes to provide better understanding of the extent of the infection in the community, and monitoring the progression of the COVID-19 epidemic. We conducted sero-prevalence study to estimate prior infection with with SARS-CoV-2 in Addis Ababa. MethodsA cross-sectional study was done from April 23 to 28, 2020 among 301 randomly selected residents of Addis Ababa; with no known history of contact with confirmed COVID-19 person. Interviews on socio demographic and behavioural risk factor followed by serological tests were performed for SARS-CoV-2 IgM, and IgG antibodies, using COVID-19 IgG/IgM Rapid Test Cassette. The test has sensitivity of 87{middle dot}9% and specificity of 100% for lgM; and a sensitivity of 97{middle dot}2% and specificity of 100% for IgG. RT-PCR test was also done on combined nasopharyngeal and oropharengeal swabs as an important public health consideration. FindingsThe unadjusted antibody-based crude SARS-CoV-2 prevalence was 7{middle dot}6% and the adjusted true SARS-CoV-2 prevalence was estimated at 8{middle dot}8% (95% CI 5{middle dot}5%-11{middle dot}6%) for the study population. Higher sero-prevalence were observed for males (9.0%), age below 50 years (8.2%), students and unemployed (15.6%), those with primary education (12.1%), smokers (7.8%), alcohol consumers (8.6%), chatt-chewers (13.6%) and shish smokers (18.8%). Seroprevalence was not significantly associated neither with socio-demographic not behavioral characteristics. According to the findings, possibly more individuals had been infected in Addis Ababa than what was being detected and reported by RT-PCR test suggestive of community transmission. The use of serological test for epidemiological estimation of the extent of SARS-CoV-2 epidemic gives a more precise estimate of magnitude which would be used for further monitoring and surveillance of the magnitude of the SARS CoV-2 infection.

microbiology↗

bioRxiv2020

Bacterial profiles and their antimicrobial susceptibility pattern of Isolates from inanimate hospital environments at Tikur Anbessa Specialized Teaching Hospital, Addis Ababa, Ethiopia

Microbial contamination of hospital environment plays an important role in the spread of health care-associated infections (HCAIs). This study was conducted to determine bacterial contamination, bacterial profiles and antimicrobial susceptibility pattern of bacterial isolates from environmental surfaces and medical equipment. A cross-sectional study was conducted at Tikur Anbessa Specialized Hospital (TASH) from June to September, 2018. A total of 164 inanimate surfaces located at intensive care units (ICUs) and operation theaters (OTs) were swabbed. All isolates were identified by using routine bacterial culture, Gram staining and a panel of biochemical tests. For each identified bacteria, antibiogram profiles were determined by the Kirby Bauer disk diffusion method according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI). Out of the 164 swabbed samples, 141 (86%) were positive for bacterial growth. The predominant bacteria identified from OTs and ICUs were S. aureus (23% vs 11.5%), Acinetobacter spp (3.8% vs 17.5%) and Coagulase negative Staphylococcus (CONS) (12.6% vs 2.7%) respectively. Linens were the most contaminated materials among items studied at the hospital (14.8%). The proportions of resistance among Gram-positive bacteria (GPB) were high for penicillin (92.8%), cefoxitin (83.5%) and erythromycin (54.1%). However, the most effective antibiotics were clindamycin with only 10.4% and 16.5% resistance rates, respectively. The antimicrobial susceptibility profiles of Gram-negative bacteria (GNB) revealed that the most effective antibiotics were amikacin, ciprofloxacin, and gentamicin with resistance rate of 25%, 37.5%, and 46.3%, respectively. However, the highest resistance was recorded against ampicillin (97.5%), ceftazidime (91.3%), ceftriaxone (91.3%) and aztreonam (90%). The inanimate surfaces near immediate patient environment and commonly touched medical equipment within OTs and ICUs are reservoirs of potential pathogenic bacteria that could predispose critically ill patients to acquire HCAIs. The proportions of antimicrobial resistance profile of the isolates are much higher from studied clean inanimate environments.

microbiology↗

bioRxiv2020

Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations

BackgroundGenetic studies of biomedical phenotypes in underrepresented populations identify disproportionate numbers of novel associations. However, current genomics infrastructure--including most genotyping arrays and sequenced reference panels--best serves populations of European descent. A critical step for facilitating genetic studies in underrepresented populations is to ensure that genetic technologies accurately capture variation in all populations. Here, we quantify the accuracy of low-coverage sequencing in diverse African populations. ResultsWe sequenced the whole genomes of 91 individuals to high-coverage ([≥]20X) from the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study, in which participants were recruited from Ethiopia, Kenya, South Africa, and Uganda. We empirically tested two data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole genome sequencing data. We show that low-coverage sequencing at a depth of [≥]4X captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1X) performed comparable to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation, with 4X sequencing detecting 45% of singletons and 95% of common variants identified in high-coverage African whole genomes. ConclusionThese results indicate that low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, including those that capture variation most common in Europeans and Africans. Low-coverage sequencing effectively identifies novel variation (particularly in underrepresented populations), and presents opportunities to enhance variant discovery at a similar cost to traditional approaches.

genomics↗