Biology subjects

Jones, D. L.

Publications and source records attributed to Jones, D. L..

26 records · Page 2Linked to original sources

bioRxiv2021

Identification and predictability of soil quality factors and indicators from conventional soil and vegetation classifications

Generally, the physical, chemical and biological attributes of a soil combined with abiotic factors (e.g. climate and topography) drive pedogenesis. However, biological indicators of soil quality play no direct role in traditional soil classification and surveys. To support their inclusion in classification schemes, previous studies have shown that soil type is a key factor determining microbial community composition in arable soils. This suggests that soil type could be used as proxy for soil biological function and vice versa. In this study we assessed the relationship between soil biological indicators with either vegetation cover or soil type. A wide range of soil attributes were measured on soils from across the UK to investigate whether; (1) appropriate soil quality factors (SQFs) and indicators (SQIs) can be identified, (2) soil classification can predict SQIs; (3) which soil quality indicators were more effectively predicted by soil types, and (4) to what extent do soil types and/ or aggregate vegetation classes (AVCs) act as major regulators of SQIs. Factor analysis was used to group 20 soil attributes into six SQFs namely; Soil organic matter, Organic matter humification, Soluble nitrogen, Microbial biomass, Reduced nitrogen and Soil humification index. Of these, Soil organic matter was identified as the most important SQF in the discrimination of both soil types and AVCs. Among the measured soil attributes constituting the Soil organic matter factor were, microbial quotient and bulk density were the most important attributes for the discrimination of both individual soil types and AVCs. The Soil organic matter factor discriminated three soil type groupings and four aggregate vegetation class groupings. Only the Peat soil and Heath and bog AVC were distinctly discriminated from other groups. All other groups overlapped with one another, making it practically impossible to define reference values for each soil type or AVC. We conclude that conventionally classified soil types cannot predict the SQIs (or SQFs), but can be used in conjunction with the conventional soil classifications to characterise the soil types. The two-way ANOVA showed that the AVCs were a better regulator of the SQIs than the soil types and that they (AVCs) presented a significant effect on the soil type differences in the measured soil attributes.

ecology↗

bioRxiv2020

Adaptation with correlated noise predicts negative interval correlations in neuronal spike trains

Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall into two categories based on the pattern of SCCs: non-bursting units have negative SCCs which remain negative but decay to zero with increasing lags (Type I SCCs), and bursting units have oscillatory (alternating sign) SCCs which damp to zero with increasing lags (Type II SCCs). Here, we predict and match observed ISI serial correlations in these afferents using a stochastic dynamic threshold model. We determine SCCs as a function of an arbitrary discrete noise correlation function Rk, where k is a multiple of the mean ISI. The function permits forward and inverse calculations of SCCs. Both types of SCCs can be generated by adding colored noise to the spike threshold with Type I SCCs generated with slow noise and Type II SCCs generated with fast noise. We show that a first-order autoregressive (AR) process with a single parameter is sufficient to predict and accurately match both types of afferent SCCs, the type being determined by the sign of the AR parameter. The predicted and experimentally observed SCCs are in geometric progression. The theory predicts that the limiting sum of SCCs is -0.5 yielding a perfect DC-block in the power spectrum of the spike train. Observed SCCs from afferents have a limiting sum that is slightly larger at -0.475 {+/-} 0.04 (mean {+/-} s.d.). We conclude that the underlying process for generating ISIs may be a simple combination of low-order autoregressive (AR) processes, and discuss the results from the perspective of optimal coding.

neuroscience↗

bioRxiv2020

Neuroglian regulates Drosophila intestinal stem cell proliferation through enhanced signaling via the Epidermal Growth Factor Receptor

The Drosophila melanogaster intestine is an excellent system for elucidating mechanisms regulating stem cell behavior under homeostatic conditions or in response to injury, stress, or ageing. Here we show that the septate junction (SJ) protein Neuroglian (Nrg) is expressed in intestinal stem cells (ISCs) and daughter enteroblasts (EBs) within the fly midgut, the equivalent of the mammalian small intestine. Although Nrg localizes to the plasma membrane, SJs are not present between ISC/EBs, suggesting Nrg plays a different role in this tissue. Generation of ISCs homozygous for a null allele of Nrg revealed that Nrg is required for ISC proliferation in young flies, and depletion of Nrg from ISCs/EBs was able to suppress the increase in ISC proliferation with age. Conversely, overexpression of Nrg in ISC/EBs was sufficient to drive ISC proliferation, leading to an increase in cells expressing ISC/EB markers. In addition, we observed an increase in EGFR activation. Genetic epistasis experiments revealed that Nrg acts upstream of EGFR in the midgut to regulate ISC proliferation. As Nrg function is highly conserved in mammalian systems, our work characterizing the role of Nrg in the intestine has implications for the etiology and treatment of intestinal disorders due to altered ISC behavior.

cell biology↗

bioRxiv2020

ZNF416 is a pivotal transcriptional regulator of fibroblast mechano-activation

Matrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly-isolated lung fibroblasts using assay for transposase-accessible chromatin followed by sequencing (ATAC-seq). We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known pro-fibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Similarly, motif analysis of the promoters of differentially expressed genes observed in freshly sorted fibroblasts from an experimental bleomycin lung fibrosis model also identified ZNF416 as a putative mediator of in vivo fibroblast activation. Genome occupancy analysis using chromatin-immunoprecipitation followed by sequencing (ChIP-seq) confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue-fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and pro-fibrotic transcriptional regulators. Using loss and gain of function studies we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis and contractile function. Together these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.

cell biology↗

bioRxiv2019

A time-resolved imaging-based CRISPRi screening method

Our ability to connect genotypic variation to biologically important phenotypes has been seriously limited by the gap between live cell microscopy and library-scale genomic engineering. Specifically, this has restricted studies of intracellular dynamics to one strain at a time and thus, generally, to the impact of genes with known function. Here we show how in situ genotyping of a library of E. coli strains after time-lapse imaging in a microfluidic device overcomes this problem. We determine how 235 different CRISPR interference (CRISPRi) knockdowns impact the coordination of the replication and division cycles of E. coli by monitoring the location of replication forks throughout on average >500 cell cycles per knockdown. The single-cell time-resolved assay allows us to determine the distribution of single-cell growth rates, cell division sizes, and replication initiation volumes. Subsequent in situ genotyping allows us to map each phenotype distribution to a specific genetic perturbation in order to determine which genes are important for cell cycle control. The technology presented in this study enables genome-scale screens of virtually all live-cell microscopy assays and, therefore, constitutes a qualitatively new approach to cellular biophysics.

biophysics↗

bioRxiv2018

Two-step concentration of complex water samples for the detection of viruses

The accurate detection and quantification of pathogenic viruses in water is essential to understand and reduce the risk of human infection. In this paper, we validated a two-step method for the concentration of enteric viruses in water and wastewater samples. The method involves a tangential flow ultrafiltration step that reduces the sample volume of 1 - 10 L to approx. 50 mL, followed by secondary precipitation using polyethylene glycol 6000 that reduces the volume to 1 - 4 mL. For method validation, surface water samples were spiked with different concentrations of enteric viruses and viral recoveries in the concentrates exceeded 10% in all experiments. The method is suitable for water samples with high and low salinity and turbidity, allowing the accurate comparison of viral titers in a diverse range of water types. Furthermore, the method has the potential to concentrate other pathogens, e.g. bacteria or protozoa. Hence, the use of this method can improve the holistic assessment of risks associated with wastewater contaminated environments.\n\nO_LIModified tangential flow ultrafiltration method that reduces membrane clogging.\nC_LIO_LISecondary concentration with a beef extract-elution step to remove solid matter.\nC_LIO_LIThe two-step concentration method enables at least 10% recovery for different enteric viruses in difficult matrices.\nC_LIO_LIUsing the two-step concentration method 10,000x concentration can be achieved.\nC_LI\n\nSpecifications Table:\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@12d4fceorg.highwire.dtl.DTLVardef@1d2880borg.highwire.dtl.DTLVardef@e1acf6org.highwire.dtl.DTLVardef@226492org.highwire.dtl.DTLVardef@1f8edf0_HPS_FORMAT_FIGEXP M_TBL C_TBL

microbiology↗

bioRxiv2017

A systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria

Gene regulation is one of the most ubiquitous processes in biology. But while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here we show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect bacterial promoters in a systematic and scalable way. We demonstrate this method on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input-output relationships. This method opens up the possibility of exhaustively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

biophysics↗

bioRxiv2017

Structural and functional diversity of a dense sample of retinal ganglion cells

To aid understanding of retinal structure and function, we present as an online resource the dendritic arbors and visual responses of ganglion cells in a single patch of mouse retina. We divide the inner plexiform layer, which contains the dendritic arbors of ganglion cells, into four sublaminae defined by a purely anatomical principle of arbor segregation. The sublaminae serve as the starting point for a hierarchical clustering of our ganglion cells. We propose and apply a quantitative criterion for validating a cluster as a ganglion cell type: the aggregate neurite density of a type should be approximately uniform (\"density conservation\"). Finally, we find that ganglion cells arborizing in the inner marginal sublamina of the inner plexi-form layer exhibit significantly more sustained visual responses on average.

neuroscience↗