The oral microbiome community variations associated with normal, potentially malignant disorders and malignant lesions of the oral cavity.

The human oral microbiome has been known to show strong association with various oral diseases including oral cancer. This study attempts to characterize the community variations between normal, oral potentially malignant disorders (OPMD) and cancer associated microbiota using 16S rDNA sequencing. Swab samples were collected from three groups (normal, OPMD and oral cancer) with nine subjects from each group. Bacteria genomic DNA was isolated in which full length 16S rDNA were amplified and used for cloned library sequencing. 16S rDNA sequences were processed and analysed with MOTHUR. A core oral microbiome was identified consisting of Firmicutes, Proteobacteria, Fusobacteria, Bacteroidetes and Actinobacteria at the phylum level while Streptococcus, Veillonella, Gemella, Granulicatella, Neisseria, Haemophilus, Selenomonas, Fusobacterium, Leptotrichia, Prevotella, Porphyromonas and Lachnoanaerobaculum were detected at the genus level. Firmicutes and Streptococcus were the predominant phylum and genus respectively. Potential oral microbiome memberships unique to normal, OPMD and oral cancer oral cavities were also identified. Analysis of Molecular Variance (AMOVA) showed a significant difference between the normal and the cancer associated oral microbiota but not between the OPMD and the other two groups. However, 2D NMDS showed an overlapping of the OPMD associated oral microbiome between the normal and cancer groups. These findings indicated that oral microbes could be potential biomarkers to distinguish between normal, OPMD and cancer subjects.

Molecular diversity of the methanotrophic bacteria communities associated with disused tin-mining ponds in Kampar, Perak, Malaysia.

In a previous study, notable differences of several physicochemical properties, as well as the community structure of ammonia oxidizing bacteria as judged by 16S rRNA gene analysis, were observed among several disused tin-mining ponds located in the town of Kampar, Malaysia. These variations were associated with the presence of aquatic vegetation as well as past secondary activities that occurred at the ponds. Here, methane oxidizing bacteria (MOB), which are direct participants in the nutrient cycles of aquatic environments and biological indicators of environmental variations, have been characterised via analysis of pmoA functional genes in the same environments. The MOB communities associated with disused tin-mining ponds that were exposed to varying secondary activities were examined in comparison to those in ponds that were left to nature. Comparing the sequence and phylogenetic analysis of the pmoA clone libraries at the different ponds (idle, lotus-cultivated and post-aquaculture), we found pmoA genes indicating the presence of type I and type II MOB at all study sites, but type Ib sequences affiliated with the Methylococcus/Methylocaldum lineage were most ubiquitous (46.7 % of clones). Based on rarefaction analysis and diversity indices, the disused mining pond with lotus culture was observed to harbor the highest richness of MOB. However, varying secondary activity or sample type did not show a strong variation in community patterns as compared to the ammonia oxidizers in our previous study.

Molecular diversity of the ammonia-oxidizing bacteria community in disused tin-mining ponds located within Kampar, Perak, Malaysia.

Disused tin-mining ponds make up a significant amount of water bodies in Malaysia particularly at the Kinta Valley in the state of Perak where tin-mining activities were the most extensive, and these abundantly available water sources are widely used in the field of aquaculture and agriculture. However, the natural ecology and physicochemical conditions of these ponds, many of which have been altered due to secondary post-mining activities, remains to be explored. As ammonia-oxidizing bacteria (AOB) are directly related to the nutrient cycles of aquatic environments and are useful bioindicators of environmental variations, the focus of this study was to identify AOBs associated with disused tin-mining ponds that have a history of different secondary activities in comparison to ponds which were left untouched and remained as part of the landscape. The 16S rDNA gene was used to detect AOBs in the sediment and water sampled from the three types of disused mining ponds, namely ponds without secondary activity, ponds that were used for lotus cultivation and post-aquaculture ponds. When the varying pond types were compared with the sequence and phylogenetic analysis of the AOB clone libraries, both Nitrosomonas and Nitrosospira-like AOB were detected though Nitrosospira spp. was seen to be the most ubiquitous AOB as it was present in all ponds types. However, AOBs were not detected in the sediments of idle ponds. Based on rarefaction analysis and diversity indices, the disused mining pond with lotus culture indicated the highest richness of AOBs. Canonical correspondence analysis indicated that among the physicochemical properties of the pond sites, TAN and nitrite were shown to be the main factors that influenced the community structure of AOBs in these disused tin-mining ponds.

Morphometric sex determination of Milky and Painted Storks in captivity.

Logistic regression was applied to develop a morphometric sexing method of two closely related stork species that were previously sexed through amplification of the CHD gene. Tarsus length (TL) and bill length (BL) measurements were recorded from captive populations of adult Milky Stork (Mycteria cinerea) (n = 60) and Painted Stork (Mycteria leucocephala) (n = 58) at Zoo Negara Malaysia. Despite having monomorphic plumages, both stork species exhibited normal sexual size dimorphism in which males were significantly larger than females in the tested variables. Based on logistic regression analysis, BL correctly classified the sex of sampled individuals from Painted and Milky stork with an overall predicted accuracy of 94.8 and 90.0%, respectively. However, TL measurements generated a lower predicted accuracy level of 86.2% and a same accuracy level of 90% on the sex classification of individuals from Painted and Milky stork, respectively. By comparing the measurements of both species, only the average BL measurements of the Milky storks were significantly lower than that of Painted storks (t-test, P80.001). The logistic regression equation in this study may serve as a simple and more practical option for sexing Milky and Painted storks for their breeding and conservation programmes.