Biology subjects

Millard, J.

Publications and source records attributed to Millard, J..

7 recordsLinked to original sources

bioRxiv2026

Creation of Novel Methylating Conjugal Donor Strains for Genetically Recalcitrant Bacteria

A methodology is presented to integrate DNA methyltransferase genes of interest into the single copy, IncP{beta} R Factor conjugal plasmid, R702. This is to enable DNA transfer, or improved frequency thereof, by mirroring the recipient native DNA methylation signature prior to transfer of plasmid DNA by conjugation, evading native restriction modification systems in the organism of study, without target strain modification. As proof of concept, the bacteriophage derived methyltransferase [FE]3TI, known to facilitate DNA transfer into the industrially important model solventogenic organism, Clostridium acetobutylicum ATCC 824, was inserted into the single copy R702 to create an in vivo methylating strain. Plasmids extracted from this strain were transferred by electroporation at a comparable frequency to the established method which uses the multi-copy accessory plasmids pAN1 or pAN2, harbouring [FE]3TI. The methodology was further exemplified and employed to enable high frequency of DNA transfer into the clinically relevant Clostridioides difficile ribotype 027 outbreak strain, R20291. The modification (hsdM) and specificity (hsdS) components of the native Type I restriction modification system of R20291 were inserted into R702 to create a functional methylating conjugal donor Escherichia coli strain. This approach of coupling methylation and the native transfer functions of R702 creates a system which can easily be mobilised into a genotypically appropriate E. coli strain; creating an in vivo methylating donor strain which may be utilized to protect and transfer DNA to the organism of study by conjugation.

microbiology↗

bioRxiv2026

Unique and overlapping behavioral effects of isoform-specific NRXN1 deletions across development

Mutations in the human neurexin 1 (NRXN1) gene are associated with neurodevelopmental disorders including autism and schizophrenia. Vertebrate NRXN1 produces three major NRXN1 isoforms, named , {beta}, and{gamma} . Human genetic data suggests that deletions located at the 5 region of the gene disrupting the isoform associate mostly with clinical behavioral deficits. Yet, 3 deletions that disrupt multiple isoforms have also been identified in clinical cases. Whether deletions that selectively affect specific NRXN1 isoforms result in specific behavioral deficits remains unclear. Here, we show that zebrafish harboring gene deletions that differentially encompass nrxn1a-, -{beta}, and/or -{gamma} display both unique and overlapping locomotion, sensorimotor behavior, and social behavior deficits. Combined, our results strongly support a model by which domain selective nrxn1 deletions predict behavioral phenotypes. Moreover, our results demonstrate compelling relationships between genotype and resulting behavioral phenotypes, providing functional insights into the complexity of NRXN1-associated neuropsychiatric behaviors.

neuroscience↗

bioRxiv2025

Large language models possess some ecologicalknowledge, but how much?

Large Language Models (LLMs) have shown remarkable capabilities in question answering across various domains, yet their effectiveness in ecological knowledge remains underexplored. Understanding their potential to recall and synthesize ecological information is crucial as AI tools become increasingly integrated into scientific workflows. Here, we assess the ecological knowledge of two LLMs, Gemini 1.5 Pro and GPT-4o, across a suite of ecologically focused tasks. These tasks evaluate an LLMs ability to predict species presence, generate range maps, list critically endangered species, classify threats, and estimate species traits. We introduce a new benchmark dataset to quantify LLM performance against expert-derived data. While the LLMs tested outperform naive baselines, achieving around 20 percent-age points higher accuracy in species presence prediction, they reach only a third of the mean F1 score for range map generation and improve threat classification by just around 10 points over random guessing. These results highlight both the promise and challenges of applying LLMs in ecology. Our findings suggest that domain-specific fine-tuning is necessary to improve eco-logical knowledge in LLMs. By providing a repeatable evaluation framework, our benchmark dataset will facilitate future research in this area, helping to refine AI applications for ecological science.

ecology↗

bioRxiv2024

Large language models help facilitate the automated synthesis of information on potential pest controllers

The body of ecological literature, which informs much of our knowledge of the global loss of biodiversity, has been experiencing rapid growth in recent decades. The increasing difficulty to synthesise this literature manually has simultaneously resulted in a growing demand for automated text mining methods. Within the domain of deep learning, large language models (LLMs) have been the subject of considerable attention in recent years by virtue of great leaps in progress and a wide range of potential applications, however, quantitative investigation into their potential in ecology has so far been lacking. In this work, we analyse the ability of GPT-4 to extract information about invertebrate pests and pest controllers from abstracts of a body of literature on biological pest control, using a bespoke, zero-shot prompt. Our results show that the performance of GPT-4 is highly competitive with other state-of-the-art tools used for taxonomic named entity recognition and geographic location extraction tasks. On a held-out test set, we show that species and geographic locations are extracted with F1-scores of 99.8% and 95.3%, respectively, and highlight that the model is able to distinguish very effectively between the primary roles of interest (predators, parasitoids and pests). Moreover, we demonstrate the ability of the model to effectively extract and predict taxonomic information across various taxonomic ranks, and to automatically correct spelling mistakes. However, we do report a small number of cases of fabricated information (hallucinations). As a result of the current lack of specialised, pre-trained ecological language models, general-purpose LLMs may provide a promising way forward in ecology. Combined with tailored prompt engineering, such models can be employed for a wide range of text mining tasks in ecology, with the potential to greatly reduce time spent on manual screening and labelling of the literature.

ecology↗

bioRxiv2020

Detection of a bedaquiline / clofazimine resistance reservoir in Mycobacterium tuberculosis predating the antibiotic era

Drug resistance in tuberculosis (TB) poses a major ongoing challenge to public health. The recent inclusion of bedaquiline into TB drug regimens has improved treatment outcomes, but this advance is threatened by the emergence of strains of Mycobacterium tuberculosis (Mtb) resistant to bedaquiline. Clinical bedaquiline resistance is most frequently conferred by off-target resistance-associated variants (RAVs) in the mmpR5 gene (Rv0678), the regulator of an efflux pump, which can also confer cross-resistance to clofazimine, another TB drug. We compiled a dataset of 3,682 Mtb genomes, including 150 carrying variants in mmpR5 that have been associated to borderline (henceforth intermediate) or confirmed resistance to bedaquiline. We identified eight cases where RAVs were present in the genomes of strains collected prior to the use of bedaquiline in TB treatment regimes. Phylogenetic reconstruction points to multiple emergence events and circulation of RAVs in mmpR5, some estimated to predate the introduction of bedaquiline. However, epistatic interactions can complicate bedaquiline drug-susceptibility prediction from genetic sequence data. Indeed, in one clade of isolates where the RAV Ile67fs is estimated to have emerged prior to the antibiotic era, co-occurrence of mutations in mmpL5 are found to neutralise bedaquiline resistance. The presence of a pre-existing reservoir of Mtb strains carrying bedaquiline RAVs prior to its clinical use augments the need for rapid drug susceptibility testing and individualised regimen selection to safeguard the use of bedaquiline in TB care and control.

genomics↗

bioRxiv2020

Evaluation of nafamostat mesylate safety and inhibition of SARS-CoV-2 replication using a 3-dimensional human airway epithelia model

In the current COVID-19 pandemic context, Ensysce and its subsidiary Covistat have been working to repurpose nafamostat mesylate as an effective oral and inhalation treatment against SARS-CoV-2 infection. Prior reports used cell lines to demonstrate the antiviral potential of nafamostat against coronaviral infections and determined its mechanism of action through inhibition of transmembrane protease serine 2 (TMPRSS2). We selected a biologically relevant pre-clinical experimental model of SARS-CoV-2 lung infection using a 3D human reconstituted airway epithelial model of nasal origin to characterize the effects of nafamostat on tissue-level cellular ultrastructure and viral infection kinetics. Our results confirm the not only the relevance of this model for the preclinical evaluation of safety and efficacy of antiviral candidates, but also the highly potent nature of nafamostat SARS-CoV-2 antiviral activity. The studies described herein provided evidence demonstrating the therapeutic potential of nafamostat against COVID-19, as well as its safety upon exposure to lung airway cellular. One Sentence SummaryUsing a human airway model, study demonstrates the powerful inhibitory effect of nafamostat on SARS-CoV-2 genome copy detection when applied apically.

cell biology↗

bioRxiv2019

N-acetyltransferase 2 genotypes amongst ulu Speaking South Africans and isoniazid / N-acetyl-isoniazid pharmacokinetics during ant-tuberculosis treatment

BackgroundDistribution of N-acetyltransferase2 (NAT2) polymorphisms varies considerably among different ethnic groups. Information on NAT2 single-nucleotide polymorphisms in South African population is limited. We investigated NAT2 polymorphisms and their effect on isoniazid pharmacokinetics in Zulu black HIV-infected South Africans in Durban, South Africa. Methods: HIV-infected participants with culture-confirmed pulmonary tuberculosis (TB) were enrolled from two unrelated studies. Culture-confirmed participants were genotyped for NAT2 polymorphisms 282C>T, 341T>C, 481C>T, 857G>A, 590G>A and 803A>G using Life Technologies pre-validated Taqman assays (Life Technologies, Paisley, UK). Participants underwent sampling for determination of plasma isoniazid and N-acetylisoniazid concentrations. ResultsAmongst the 120 patients, 63/120 (52.5%) were slow metabolisers (NAT2*5/*5), 43/120 (35.8%) had intermediate (NAT2*5/12), and 12/120 (11.7%) had rapid genotype (NAT2*4/*11, NAT2*11/12 and NAT2*12/12). NAT2 alleles in this study were *4, *5C, *5D, *5E, *5J, *5K, *5KA, *5T, *11A, *12A/12C and *12M. NAT2*5 was the most frequent allele (70.4%) followed by NAT2*12 (27.9%). 34/40 had both PK results and NAT2 genotyping results. The median area under the concentration-time-curve to infinity (AUC0-{infty}) interquartile range (IQR) was 7.81 (5.87 - 16.83) g/ml/hr and maximum concentration (Cmax) 3.14 g/ml (2.42 - 4.36) g/mL. Individual polymorphisms were not equally distributed, with some represented in small numbers. Genotype did not correlate with phenotype, rapid genotype showing higher AUC0-{infty} than slow but not significant, p=0.43. ConclusionThere was high prevalence of slow followed by intermediate then rapid acetylator genotypes. The poor concordance between genotype and phenotype suggests that other factors or genetic loci influence INH metabolism, and warrants further investigation in this population.

genetics↗