Biology subjects

Pillay, S.

Publications and source records attributed to Pillay, S..

9 recordsLinked to original sources

bioRxiv2025

A comparative metagenomic analysis of antibiotic resistance in the fecal microbiome of pigs raised with and without antibiotics

PurposeThe use of antibiotics in swine production has raised concerns about its impact on animal health, microbial ecology, and the emergence of antibiotic resistance. The gut microbiome, a critical component of animal health, is susceptible to disruptions caused by antibiotic use. The fecal microbiome can provide a snapshot of changes in the gut microbiome and provide information on the spread of antibiotic resistance from pig feces to the environment. MethodsWe investigated the differences between the fecal microbiome of pigs raised with (AB+) and without (AB-) antibiotics to assess how antibiotic exposure influenced the microbial community, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs). ResultsOur findings revealed that the use of antibiotics combined with study-specific conditions alters the fecal microbiome. Antibiotic usage in pigs explains 20% of the variation in the diversity of bacterial species detected between AB+ and AB- pigs. Similarly, variations in ARGs were observed in the two groups. The RND efflux pump gene family was abundant in both groups. The OXA {beta}-lactamase gene and associated plasmids were more prevalent in the AB- group. We also identified integrons linked to chloramphenicol resistance and transposon-associated integrative elements that can facilitate the spread of antibiotic resistance genes within and between bacterial species. ConclusionThese findings highlight that antibiotics influence both the microbial community and the antibiotic resistance gene repertoire, regardless of study-specific or environmental conditions. This emphasises the potential for fecal matter to contribute to the spread of antibiotic resistance in the environment, underscoring the need for more research to fully understand these dynamics in agricultural settings.

microbiology↗

bioRxiv2024

Predicted meta-omics: a potential solution to multi-omics data scarcity in microbiome studies

Imbalances in the gut microbiome have been linked to conditions such as inflammatory bowel disease, diabetes, and cancer. While metagenomics and amplicon sequencing are commonly used to study the microbiome, they do not capture all layers of microbial functions. Other meta-omics data can provide more insights, but these are more costly and laborious to procure. The growing availability of paired meta-omics data offers an opportunity to develop machine learning models that can infer connections between metagenomics data and other forms of meta-omics data, enabling the prediction of these other forms of meta-omics data from metagenomics. We evaluated several machine learning models for predicting meta-omics features from various meta-omics inputs. Simpler architectures such as elastic net regression and random forests generated reliable predictions of transcript and metabolite abundances, with correlations of up to 0.77 and 0.74, respectively, but predicting protein profiles was more challenging. We also identified a core set of well-predicted features for each meta-omics output type, and showed that multi-output regression neural networks performed similarly when trained using fewer output features. Lastly, our experiments demonstrated that predicted features can be used for the downstream task of inflammatory bowel disease classification, with performance comparable to that of experimental data.

microbiology↗

bioRxiv2024

Neuroligin 3 highlights sexually dimorphic circuitry in Drosophila social spacing

In Drosophila melanogaster, the autism-related Neuroligin 3 (Nlg3) protein is a postsynaptic membrane protein important for synapse development and regulation, which plays a role in social spacing behaviour. Here, we report the localization of Nlg3 to the calyx of the mushroom bodies (MB), optic lobes (OL), and protocerebral bridge (PB). Using RNA interference, nlg3 knockdown in each of these structures recapitulated the effect of knocking down it in all nlg-3 neurons. Hyperactivation and silencing of these neurons in the MB, but not the PB, controls social space in males and females, while hyperactivating and silencing of all nlg3-expressing neurons, including within the MB, PB, and OL, regulates male and female social space. Knocking down neurotransmitter biosynthesis enzymes, which decreases the amount of neurotransmitter release, showed that reducing acetylcholine release from the MB decreased female social space, whereas knocking down any dopamine receptor in the MB increased male social space. Lastly, to investigate the sexually dimorphic effects on social spacing previously seen in nlg3 mutants, we examined a subset of sexually dimorphic fruitless-expressing (fru)P1 neurons known to regulate sexually dimorphic behaviours. Hyperactivation of those fruP1 neurons decreased social space in both sexes, while silencing those fruP1 neurons specifically increased male social space without affecting females. Our findings highlight a sex-specific social space neural circuitry that includes the OL, MB, and fruP1 neurons, while uncovering the underlying basis of some of the sex differences in this behaviour. Article SummaryIn vinegar flies (Drosophila melanogaster), the autism-related Neuroligin 3 protein (Nlg3) controls neuronal development and regulation but also affects fly social behaviour. Nlg3 is localized to the mushroom bodies (MB), protocerebral bridge, and the optic lobes. We show that those structures are important in determining social space in a sex dependant manner. In addition, reducing acetylcholine release from the MB affects female social space, while reducing dopamine receptors of the MB only affect male behaviour. Finally, the fruitless sexually dimorphic neurons control social behavior differently in males and females.

animal behavior and cognition↗

bioRxiv2024

Portable In-Field DNA Sequencing for Rapid Detection of Pathogens and Antimicrobial Resistance: A Proof-of-Concept Study

PurposeInfectious diseases represent a major global health threat due to the rapid spread of pathogens, leading to widespread outbreaks. Concurrently, antimicrobial resistance (AMR) is increasing, making standard treatments less effective and complicating infection management. Effective surveillance systems are essential to address these challenges. MethodsWe conducted a proof-of-concept study to evaluate a portable in-field microbial lab against a traditional molecular lab for DNA isolation, sequencing, microbial detection, antibiotic resistance gene identification, and plasmid classification. Samples from lake water, wastewater treatment plant sludge, and retail meat were selected to reflect relevant surveillance vectors. This approach provides valuable data for environmental monitoring, public health, and food safety, aiding in outbreak preparedness. We compared results using five metrics: DNA yield and purity, read N50, taxonomic classification, antibiotic resistance gene identification (ARGs), and plasmid classification. ResultsOur study found that metagenomic bacterial DNA isolation from environmental and food sources is feasible with portable lab technology, producing [≥]800ng of DNA, suitable for Nanopore sequencing. DNA from retail meat, lake, and sludge samples resulted in similar read numbers and read N50 values. Taxonomic classification was achieved at the genus and species levels. A Jaccard similarity of over 50% was observed in the top 20 most abundant species between chicken samples, and lake samples. ESKAPE pathogens were detected in chicken and lake samples. ARGs and plasmids were also identified in both retail meat and lake samples. ConclusionThis study demonstrates that in-field DNA isolation and sequencing are feasible with minimal equipment, yielding results comparable to traditional lab methods.

microbiology↗

bioRxiv2024

A Metagenomic Study of Antibiotic Resistance Across Diverse Soil Types and Geographical Locations

BackgroundSoil naturally harbours antibiotic resistant bacteria and is considered to be a reservoir for antibiotic resistance. The overuse of antibiotics across human, animal, and environmental sectors has intensified this issue leading to an increased acquisition of antibiotic resistant genes by bacteria in soil. Various biogeographical factors, such as soil pH, temperature, and pollutants, play a role in the spread and emergence of antibiotic resistance in soil. In this study, we utilised publicly available metagenomic datasets from four different soil types (rhizosphere, urban, natural, and rural areas) sampled from nine distinct geographic locations to explore the patterns of antibiotic resistance in soils from different regions. ResultsBradyrhizobium was predominant in vegetation soil types regardless of soil pH and temperature. ESKAPE pathogen Pseudomonas aeruginosa was prevalent in rural soil samples. Antibiotic resistance gene families such as 16s rRNA with mutations conferring resistance to aminoglycoside antibiotics, OXA {beta}-lactamase, ANT(3), and the RND and MFS efflux pump gene were identified in all soil types, with their abundances influenced by anthropogenic activities, vegetation, and climate in different geographical locations. Plasmids were more abundant in rural soils and were linked to aminoglycoside resistance. Integrons and integrative elements identified were associated with commonly used and naturally occurring antibiotics, showing similar abundances across different soil types and geographical locations. ConclusionAntimicrobial resistance in soil may be driven by anthropogenic activities and biogeographical factors, increasing the risk of bacteria developing resistance and leading to higher morbidity and mortality rates in humans and animals.

microbiology↗

bioRxiv2023

When do longer reads matter? A benchmark of long read de novo assembly tools for eukaryotic genomes

BackgroundAssembly algorithm choice should be a deliberate, well-justified decision when researchers create genome assemblies for eukaryotic organisms from third-generation sequencing technologies. While third-generation sequencing by Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) have overcome the disadvantages of short read lengths specific to next-generation sequencing (NGS), third-generation sequencers are known to produce more error-prone reads, thereby generating a new set of challenges for assembly algorithms and pipelines. Since the introduction of third-generation sequencing technologies, many tools have been developed that aim to take advantage of the longer reads, and researchers need to choose the correct assembler for their projects. ResultsWe benchmarked state-of-the-art long-read de novo assemblers, to help readers make a balanced choice for the assembly of eukaryotes. To this end, we used 13 real and 72 simulated datasets from different eukaryotic genomes, with different read length distributions, imitating PacBio CLR, PacBio HiFi, and ONT sequencing to evaluate the assemblers. We include five commonly used long read assemblers in our benchmark: Canu, Flye, Miniasm, Raven and Redbean. Evaluation categories address the following metrics: reference-based metrics, assembly statistics, misassembly count, BUSCO completeness, runtime, and RAM usage. Additionally, we investigated the effect of increased read length on the quality of the assemblies, and report that read length can, but does not always, positively impact assembly quality. ConclusionsOur benchmark concludes that there is no assembler that performs the best in all the evaluation categories. However, our results shows that overall Flye is the best-performing assembler, both on real and simulated data. Next, the benchmarking using longer reads shows that the increased read length improves assembly quality, but the extent to which that can be achieved depends on the size and complexity of the reference genome.

bioinformatics↗

bioRxiv2020

Whole Genome Sequencing of SARS-CoV-2: Adapting Illumina Protocols for Quick and Accurate Outbreak Investigation During a Pandemic

The COVID-19 pandemic spread very fast around the world. A few days after the first detected case in South Africa, an infection started a large hospital outbreak in Durban, KwaZulu-Natal. Phylogenetic analysis of SARS-CoV-2 genomes can be used to trace the path of transmission within a hospital. It can also identify the source of the outbreak and provide lessons to improve infection prevention and control strategies. In this manuscript, we outline the obstacles we encountered in order to genotype SARS-CoV-2 in real-time during an urgent outbreak investigation. In this process, we encountered problems with the length of the original genotyping protocol, reagent stockout and sample degradation and storage. However, we managed to set up three different library preparation methods for sequencing in Illumina. We also managed to decrease the hands on library preparation time from twelve to three hours, which allowed us to complete the outbreak investigation in just a few weeks. We also fine-tuned a simple bioinformatics workflow for the assembly of high-quality genomes in real-time. In order to allow other laboratories to learn from our experience, we released all of the library preparation and bioinformatics protocols publicly and distributed them to other laboratories of the South African Network for Genomics Surveillance (SANGS) consortium.

genomics↗

bioRxiv2020

The Neuroanatomy of Speech Processing: A Large-Scale Lesion Study

The neural basis of language has been studied for centuries, yet the networks critically involved in simply identifying or understanding a spoken word remain elusive. Several functional-anatomical models of critical neural substrates of receptive speech have been proposed, including (1) auditory-related regions in the left mid-posterior superior temporal lobe, (2) motor-related regions in the left frontal lobe (in normal and/or noisy conditions), the left anterior superior temporal lobe, or (4) bilateral mid-posterior superior temporal areas. One difficulty in comparing these models is that they often focus on different aspects of the sound-to-meaning pathway and are supported by different types of stimuli and tasks. Two auditory tasks that are typically used in separate studies--syllable discrimination and word comprehension--often yield different conclusions. We assessed syllable discrimination (words and nonwords) and word comprehension (clear speech and with a noise masker) in 158 individuals with focal brain damage: left (n=113) or right (n=19) hemisphere stroke, left (n=18) or right (n=8) anterior temporal lobectomy, and 26 neurologically-intact controls. Discrimination and comprehension tasks are doubly dissociable both behaviorally and neurologically. In support of a bilateral model, clear speech comprehension was near ceiling in 95% of left stroke cases and right temporal damage impaired syllable discrimination. Lesion-symptom mapping analyses for the syllable discrimination and noisy word comprehension tasks each implicated most of the left superior temporal gyrus (STG). Comprehension but not discrimination tasks also implicated the left pMTG, while discrimination but not comprehension tasks also implicated more dorsal sensorimotor regions in posterior perisylvian cortex.

neuroscience↗

bioRxiv2020

Antisense ncRNAs during early vertebrate development are divided in groups with distinct features

Long non-coding RNAs or lncRNAs are a broad class of non-protein coding RNAs that are >200nucleotides in length. A number of lncRNAs are shown to play an important role in gene expression regulation. LncRNAs antisense to a protein-coding gene can act either as positive or negative regulators of overlapping protein-coding mRNAs. Almost 50% of lncRNAs present during development of vertebrates such as zebrafish are of antisense lncRNA class. However, their role in gene expression regulation during development remains enigmatic. To understand the role of antisense lncRNAs in early vertebrate development, we took a computational biology approach to analyze existing as well as novel dataset. Our analysis of RNA sequencing data from zebrafish development indicates that antisense RNAs can be divided into two major classes based on their positive or negative co-expression patterns to the sense protein-coding genes. The ones with negative co-expression patterns or group-1 are maternal antisense lncRNAs that overlap mainly developmental genes. Group-2 with positive expression pattern overlap mainly house-keeping genes. Group-1 antisense lncRNAs are longer and more stable as compared to antisense lncRNAs in group-2. In addition, to answer if antisense RNAs in the two groups are differently localized in cell compartments, we deep-sequenced RNA from cytoplasmic and nuclear compartments during early developmental stages. The analysis of these compartment specific datasets revealed group-1 lncRNAs are cytosolic. Based on the cytosolic nature of group-1 RNAs and their higher complementarity to the overlapping developmental mRNAs, we speculate that the group-1 RNAs might function similar to microRNAs in silencing spurious expression of developmental genes. Group-1 and group-2 RNAs are also distinct in terms of their genomic configuration, conservation, length and transcriptional regulation. These results are not only important in understanding the role of antisense RNAs in development but also for predicting the nature of association between antisense lncRNA and overlapping protein-coding genes.

genomics↗