Biology subjects

Dillon, M. R.

Publications and source records attributed to Dillon, M. R..

5 recordsLinked to original sources

bioRxiv2020

A viral histone-like protein exploits H1-HMGB1 antagonism for chromatin invasion

Virus infection necessarily requires redirecting cellular resources towards viral progeny production. Adenovirus encodes the histone-like protein VII that causes catastrophic global reorganization of host chromatin to promote virus infection. Protein VII recruits the family of high mobility group box (HMGB) proteins to chromatin along with the histone chaperone SET. As a consequence of this recruitment, we find that protein VII causes chromatin-depletion of several linker histone H1 isoforms. The relationship between linker histone H1 and the functionally opposite HMGB proteins is critical for higher order chromatin structure. However, the physiological consequences of perturbing this relationship are largely unknown. Here, we employ complementary systems in Saccharomyces cerevisiae and human cells to demonstrate that adenovirus protein VII disrupts the H1-HMGB balance to obstruct the cell cycle. We find that protein VII causes an accumulation of G2/M cells both in yeast and human systems, underscoring the high conservation of this chromatin vulnerability. In contrast, adenovirus E1A and E1B proteins are well-established to override cell cycle regulation and promote transformation of human cells. Strikingly, we find that protein VII obstructs the cell cycle even in the presence of E1A and E1B, suggesting that protein VII-directed cell cycle disruption ensures host resources are directed towards viral proliferation during infection. Together, our results demonstrate that protein VII targets H1-HMGB1 antagonism to obstruct cell cycle progression, revealing an unexpected chromatin vulnerability exploited for viral benefit.

microbiology↗

bioRxiv2020

RESCRIPt: Reproducible sequence taxonomy reference database management for the masses

BackgroundNucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardizations limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a software package for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. ResultsTo highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA, and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. ConclusionsRESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

bioinformatics↗

bioRxiv2019

Microbiotyping the sinonasal microbiome

This study offers a novel description of the sinonasal microbiome, through an unsupervised machine learning approach combining dimensionality reduction and clustering. We apply our method to the International Sinonasal Microbiome Study (ISMS) dataset of 410 sinus swab samples. We propose three main sinonasal microbiotypes or states: the first is Corynebacterium-dominated, the second is Staphylococcus-dominated, and the third dominated by the other core genera of the sinonasal microbiome (Streptococcus, Haemophilus, Moraxella, and Pseudomonas). The prevalence of the three microbiotypes studied did not differ between healthy and diseased sinuses, but differences in their distribution were evident based on geography. We also describe a potential reciprocal relationship between Corynebacterium species and Staphylococcus aureus, suggesting that a certain microbial equilibrium between various players is reached in the sinuses. We validate our approach by applying it to a separate 16S rRNA gene sequence dataset of 97 sinus swabs from a different patient cohort. Sinonasal microbiotyping may prove useful in reducing the complexity of describing sinonasal microbiota. It may drive future studies aimed at modeling microbial interactions in the sinuses and in doing so may facilitate the development of a tailored patient-specific approach to the treatment of sinus disease in the future.

microbiology↗

bioRxiv2019

The international sinonasal microbiome study (ISMS): a multi centre, international characterization of sinonasal bacterial ecology

The sinonasal microbiome remains poorly defined, with our current knowledge based on a few cohort studies whose findings are inconsistent. Furthermore, the variability of the sinus microbiome across geographical divides remains unexplored. We characterise the sinonasal microbiome and its geographical variations in both health and disease using 16S rRNA gene sequencing of 410 individuals from across the world. Although the sinus microbial ecology is highly variable between individuals, we identify a core microbiome comprised of Corynebacterium, Staphylococcus, Streptococcus, Haemophilus, and Moraxella species in both healthy and chronic rhinosinusitis (CRS) cohorts. Corynebacterium (mean relative abundance = 44.02%) and Staphylococcus (mean relative abundance = 27.34%) appear particularly dominant in the majority of patients sampled. There was a significant variation in microbial diversity between countries (p = 0.001). Amongst patients suffering from CRS with nasal polyps, a significant depletion of Corynebacterium (40.29% vs 50.43%; p = 0.02) and over-representation of Streptococcus (7.21% vs 2.73%; p = 0.032) was identified. The delineation of the sinonasal microbiome and standardised methodology described within our study will enable further characterisation and translational application of the sinus microbiota.

microbiology↗

bioRxiv2017

The statistical nature of geometric reasoning

Geometric reasoning has an inherent dissonance: its abstract axioms and propositions refer to infinitesimal points and infinite straight lines while our perception of the physical world deals with fuzzy dots and curved stripes. How we use these disparate mechanisms to make geometric judgments remains unresolved. Here, we deploy a classically used cognitive geometric task - planar triangle completion - to study the statistics of errors in the location of the missing vertex. Our results show that the mean location has an error proportional to the side of the triangle, the standard deviation is sub-linearly dependent on the side length, and has a negative skewness. These scale-dependent responses directly contradict the conclusions of recent cognitive studies that innate Euclidean rules drive our geometric judgments. To explain our observations, we turn to a perceptual basis for geometric reasoning that balances the competing effects of local smoothness and global orientation of extrapolated trajectories. The resulting mathematical framework captures our observations and further predicts the statistics of the missing angle in a second triangle completion task. To go beyond purely perceptual geometric tasks, we carry out a categorical version of triangle completion that asks about the change in the missing angle after a change in triangle shape. The observed responses show a systematic scale-dependent discrepancy at odds with rule-based Euclidean reasoning, but one that is completely consistent with our framework. All together, our findings point to the use of statistical dynamic models of the noisy perceived physical world, rather than on the abstract rules of Euclid in determining how we reason geometrically.

animal behavior and cognition↗