Bacteria in the oral cavity of individuals consuming intoxicating substances.

Food habits and oral hygiene are critical attributes for physiochemical environment of the oral cavity. Consumption of intoxicating substances such as betel nut ('Tamul'), alcohol, smoking and chewing tobacco may strongly influence the oral ecosystem including commensal microbes. Therefore, a comparative assessment of microbes in the oral cavity between individuals consuming intoxicating substances and non-consumers may indicate the influence of these substances. Oral swabs were collected from consumers of intoxicating substances and non- consumers of Assam, India, microbes were isolated by culturing on Nutrient agar and identified by phylogenetic analysis of their 16S rRNA gene sequences. The risks of consumption of intoxicating substance on occurrence of microbes and health conditions were estimated using binary logistic regression. Mostly pathogens and opportunistic pathogens were found in the oral cavity of consumers and oral cancer patients which included Pseudomonas aeruginosa, Serratia marcescens, Rhodococcus antrifimi, Paenibacillus dendritiformis, Bacillus cereus, Staphylococcus carnosus, Klebsiella michiganensis and Pseudomonas cedrina. Enterobacter hormaechei was found in the oral cavity of cancer patients but not in other cases. Pseudomonas sp. were found to be widely distributed. The risk of occurrence of these organisms were found in between 0.01 and 2.963 odds and health conditions between 0.088 and 10.148 odds on exposure to different intoxicating substances. When exposed to microbes, the risk of varying health conditions ranged between 0.108 and 2.306 odds. Chewing tobacco showed a higher risk for oral cancer (10.148 odds). Prolonged exposure to intoxicating substances conduce a favorable environment for the pathogens and opportunistic pathogens to colonize in the oral cavity of individuals consuming intoxicating substances

Genetic Diversity of <i>Mycobacterium tuberculosis</i> Isolates from Assam, India: Dominance of Beijing Family and Discovery of Two New Clades Related to CAS1_Delhi and EAI Family Based on Spoligotyping and MIRU-VNTR Typing

<div><p>Tuberculosis (TB) is one of the major public health concerns in Assam, a remote state located in the northeastern (NE) region of India. The present study was undertaken to explore the circulating genotypes of <i>Mycobacterium tuberculosis</i> complex (MTBC) in this region. A total of 189 MTBC strains were collected from smear positive pulmonary tuberculosis cases from different designated microscopy centres (DMC) from various localities of Assam. All MTBC isolates were cultured on Lowenstein-Jensen (LJ) media and subsequently genotyped using spoligotyping and 24-loci mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) typing. Spoligotyping of MTBC isolates revealed 89 distinct spoligo patterns. The most dominant MTBC strain belonged to Beijing lineage and was represented by 35.45% (n = 67) of total isolates, followed by MTBC strains belonging to Central Asian-Delhi (CAS/Delhi) lineage and East African Indian (EAI5) lineage. In addition, in the present study 43 unknown spoligo patterns were detected. The discriminatory power of spoligotyping was found to be 0.8637 based on Hunter Gaston Discriminatory Index (HGDI). On the other hand, 24-loci MIRU-VNTR typing revealed that out of total 189 MTBC isolates from Assam 185 (97.9%) isolates had unique MIRU-VNTR profiles and 4 isolates grouped into 2 clusters. Phylogenetic analysis of 67 Beijing isolates based on 24-loci MIRU-VNTR typing revealed that Beijing isolates from Assam represent two major groups, each comprising of several subgroups. Neighbour-Joining (NJ) phylogenetic tree analysis based on combined spoligotyping and 24-loci MIRU-VNTR data of 78 Non-Beijing isolates was carried out for strain lineage identification as implemented by MIRU-VNTR<i>plus</i> database. The important lineages of MTBC identified were CAS/CAS1_Delhi (41.02%, n = 78) and East-African-Indian (EAI, 33.33%). Interestingly, phylogenetic analysis of orphan (23.28%) MTBC spoligotypes revealed that majority of these orphan isolates from Assam represent two new sub-clades Assam/EAI and Assam/CAS. The prevalence of multidrug resistance (MDR) in Beijing and Non-Beijing strains was found to be 10.44% and 9.01% respectively. In conclusion, the present study has shown the predominance of Beijing isolates in Assam which is a matter of great concern because Beijing strains are considered to be ecologically more fit enabling wider dissemination of <i>M</i>. <i>tuberculosis</i>. Other interesting finding of the present study is the discovery of two new clades of MTBC isolates circulating in Assam. More elaborate longitudinal studies are required to be undertaken in this region to understand the transmission dynamics of MTBC.</p></div

Genotypic diversity of 78 Non-Beijing and Non-orphan MTBC isolates from Assam.

<p>A MIRU-VNTR based dendrogram was generated using NJ tree analysis. <i>M</i>. <i>tuberculosis</i> strain lineages were identified using MIRU-VNTR<i>plus</i> identification database. 24-loci MIRU-VNTR alleles and spoligotypes from 78 isolates are also represented along with MIRU-VNTR NJ tree.</p

Neighbour-Joining (NJ) tree showing genetic diversity of 67 Beijing isolates from Assam based on 24 MIRU-VNTR loci.

<p>Two major clusters (Group A and Group B) and their sub-lineages can be seen from this figure.</p

Fig 7 showing phylogenetic relationship of orphan strains of MTBC from Assam with reference MTBC isolates available at the database MIRU-VNTR<i>plus</i>.

<p>The NJ tree was constructed using 24-loci MIRU-VNTR data. 24-loci MIRU-VNTR alleles and spoligotypes from 44 isolates are also represented along with MIRU-VNTR NJ tree. This phylogenetic tree clearly shows that the orphan strains of MTBC from Assam represent two new well defined sub-clades namely Assam/EAI and Assam/CAS.</p

Spoligotype patterns of MTBC circulating in Assam.

<p>Spoligotype patterns of MTBC circulating in Assam.</p

A three dimensional scatter plot based on principal component analysis (PCA) showing relatedness of different geographical regions based on their similarity in patterns of 12-loci MIRU-VNTR diversity in MTBC from Assam and other geographical localities.

<p>Different geographical areas were clustered in three groups and the state of Assam clustered with other Asian countries.</p

Comparison of Beijing MTBC isolates from Assam with Beijing isolates from other countries (Singapore, Cambodia, Hong Kong, China, Taiwan, South Africa and rest of India) where Beijing isolates are also reported.

<p>The radiation tree was constructed based on 24-MIRU-VNTR loci data using Neighbour-Joining method. Beijing isolates from Assam group into two well defined clusters, one major MTBC cluster which is close to some Beijing strains from Hong Kong, China, Taiwan and rest of India whereas the Beijing strains in the minor cluster were phylogenetically more close to a few Beijing strains from South Africa and Taiwan.</p

A two dimensional scatter plot based on principal component analysis (PCA).

<p>Geographical regions having similarity in patterns of spoligotypes tend to clusters together.</p

Recurrence of pulmonary tuberculosis in India: Findings from the 2019-2021 nationwide community-based TB prevalence survey.

Recurrent Tuberculosis patients contribute to a significant proportion of TB burden in India. A nationwide survey was conducted during 2019-2021 across India among adults to estimate the prevalence of TB. A total of 322480 individuals were screened and 1402 were having TB. Of this, 381 (27.1%) had recurrent TB. The crude prevalence (95% CI) of recurrent TB was 118 (107-131) per 100,000 population. The median duration between episodes of TB was 24 months. The proportion of drug resistant TB was 11.3% and 3.6% in the recurrent group and new TB patients respectively. Higher prevalence of recurrent TB was observed in elderly, males, malnourished, known diabetics, smokers, and alcohol users. (p<0.001). To prevent TB recurrence, all treated tuberculosis patients must be followed at least for 24 months, with screening for Chest X-ray, liquid culture every 6 months, smoking cessation, alcohol cessation, nutritional interventions and good diabetic management