Biology subjects

Barrett, D. A.

Publications and source records attributed to Barrett, D. A..

5 recordsLinked to original sources

bioRxiv2024

Investigative power of Genomic Informational Field Theory (GIFT) relative to GWAS for genotype-phenotype mapping

Identifying associations between phenotype and genotype is the fundamental basis of genetic analyses. Inspired by frequentist probability and the work of R.A. Fisher, genome-wide association studies (GWAS) extract information using averages and variances from genotype-phenotype datasets. Averages and variances are legitimated upon creating distribution density functions obtained through the grouping of data into categories. However, as data from within a given category cannot be differentiated, the investigative power of such methodologies is limited. Genomic Informational Field Theory (GIFT) is a method specifically designed to circumvent this issue. The way GIFT proceeds is opposite to that of GWAS. Whilst GWAS determines the extent to which genes are involved in phenotype formation (bottom-up approach), GIFT determines the degree to which the phenotype can select microstates (genes) for its subsistence (top-down approach). Doing so requires dealing with new genetic concepts, a.k.a. genetic paths, upon which significance levels for genotype-phenotype associations can be determined. By using different datasets obtained in ovis aries related to bone growth (Dataset-1) and to a series of linked metabolic and epigenetic pathways (Dataset-2), we demonstrate that removing the informational barrier linked to categories enhances the investigative and discriminative powers of GIFT, namely that GIFT extracts more information than GWAS. We conclude by suggesting that GIFT is an adequate tool to study how phenotypic plasticity and genetic assimilation are linked. NEW & NOTEWORTHYThe genetic basis of complex traits remains challenging to investigate using classic GWASs. Given the success of gene editing technologies this point needs to be addressed urgently since there can only be useful editing technologies if precise genotype-phenotype mapping information is available initially. GIFT is a new mapping method designed to increase the investigative power of biological/medical datasets suggesting, in turn, the need to rethink the conceptual bases of quantitative genetics.

genetics↗

bioRxiv2022

Antimicrobial resistance in dairy slurry tanks: a critical point for measurement and control

Waste from dairy production is one of the worlds largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs). However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with >99% reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for prevalence and control of AMR, and that measures to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

microbiology↗

bioRxiv2020

Anti-biofilm efficacy of a medieval treatment for bacterial infection requires the combination of multiple ingredients.

Novel antimicrobials are urgently needed to combat the increasing occurrence of drug-resistant bacteria and to overcome the inherent difficulties in treating biofilm-associated infections. Research into natural antimicrobials could provide candidates to fill the antibiotic discovery gap, and the study of plants and other natural materials used in historical infection remedies may enable further discoveries of natural products with useful antimicrobial activity. We previously reconstructed a 1,000-year-old remedy containing onion, garlic, wine, and bile salts, which is known as Balds eyesalve, and showed it to have promising antibacterial activity. In this paper, we have found this remedy has bactericidal activity against a range of Gram-negative and Gram-positive wound pathogens in planktonic culture and, crucially, that this activity is maintained against Acinetobacter baumannii, Stenotrophomonas maltophilia, Staphylococcus aureus, Staphylococcus epidermidis and Streptococcus pyogenes in a model of soft-tissue wound biofilm. While the presence of garlic in the mixture is sufficient to explain activity against planktonic cultures, garlic alone has no activity against biofilms. We have found the potent anti-biofilm activity of Balds eyesalve cannot be attributed to a single ingredient and requires the combination of all ingredients to achieve full activity. Our work highlights the need to explore not only single compounds but also mixtures of natural products for treating biofilm infections. These results also underline the importance of working with biofilm models when exploring natural products for the anti-biofilm pipeline. ImportanceBacteria can live in two ways, as individual planktonic cells or as a multicellular biofilm. Biofilm helps protect bacteria from antibiotics and makes them much harder to treat. Both the biofilm lifestyle and the evolution of antibiotic resistance mean we urgently need new drugs to treat infections. Here, we show that a medieval remedy made from onion, garlic, wine, and bile can kill a range of problematic bacteria grown both planktonically and as biofilms. A single component of the remedy - allicin, derived from garlic - is sufficient to kill planktonic bacteria. However, garlic or allicin alone do nothing against bacteria when they form a biofilm. All four ingredients are needed to fully kill bacterial biofilm communities, hinting that these ingredients work together to kill the bacteria. This suggests that future discovery of antibiotics from natural products could be enhanced by studying combinations of ingredients, rather than single plants or compounds.

microbiology↗

bioRxiv2020

Assessing the impact of physicochemical parameters in the predictive capabilities of thermodynamics-based stoichiometric approaches under mesophilic and thermophilic conditions

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed. Author summaryBiotechnology has benefitted from the development of high throughput methods characterising living systems at different levels (e.g. concerning genes or proteins), allowing the industrial production of chemical commodities. Recently, focus has been placed on determining reaction rates (or metabolic fluxes) in the metabolic network of certain microorganisms, in order to identify bottlenecks hindering their exploitation. Two main approaches are commonly used, termed metabolic flux analysis (MFA) and flux balance analysis (FBA), based on measuring and estimating fluxes, respectively. While the influence of thermodynamics in living systems was accepted several decades ago, its application to study biochemical networks has only recently been enabled. In this sense, a multitude of different approaches constraining well-established modelling methods with thermodynamics has been suggested. However, physicochemical parameters are generally not properly adjusted to the experimental conditions, which might affect their predictive capabilities. In this study, we have explored the reliability of currently available tools by investigating the impact of varying said parameters in the simulation of metabolic fluxes and metabolite concentration values. Additionally, our in-depth analysis allowed us to highlight limitations and potential solutions that should be considered in future studies.

systems biology↗

bioRxiv2019

Nuclear poly(A) tail size is regulated by Cnot1 during the serum response

The poly(A) tail removal from mRNAs introduces a delay between mRNA synthesis and decay. We measured levels and poly(A) tail sizes of serum-induced mRNAs and used mathematical modelling to compare their deadenylation time with the delay in decay and found that they are indeed correlated. Discrepancies between our data and the polyadenylation models at later time points after the peak of induction led us to investigate the size of the poly(A) tails on newly made mRNA. Surprisingly, new serum-induced mRNAs synthesised late in induction had short poly(A) tails (around A25) in the nucleus. In addition, newly made constitutive mRNAs had medium sized poly(A) tails (around A50). To see if deadenylation was responsible for the new short poly(A) tails, we depleted Cnot1, a subunit of the CCR4/NOT deadenylase. Cnot1 depletion led to slower deadenylation of cytoplasmic mRNAs, as expected, but also decreased transcription and led to longer nuclear mRNA poly(A) tails. These observations implicate CCR4/NOT in regulating both the transcription and the nuclear poly(A) tail size of serum-induced mRNAs. Detection of some chromatin-associated mRNAs with long poly(A) tails suggested that nuclear deadenylation is an early event. Our data show that initial poly(A) tail size of mRNAs can be regulated and is not always 200-250 nucleotides, adding a novel layer to the control of gene expression.

molecular biology↗