Characterization of Early Biofilm Formation and Physiology in \u3ci\u3eNeisseria gonorrhoeae\u3c/i\u3e

Many bacteria rely on the dynamics of their extracellular appendages to perform important tasks, like motility and biofilm formation. Interestingly, these dynamics have been linked to physiological responses in some pathogenic bacteria; therefore, it is important to understand more about the role of physical forces in bacteria. I used the causative agent of the human disease gonorrhea, Neisseria gonorrhoeae, as a model system to study the role of physical force on early biofilm formation. The advantage of this system is that cell-cell interactions are controlled by extracellular filaments called type IV pili (tfp). Tfp is composed of monomers that give bacteria the ability to produce a dynamic filament undergoing cycles of elongations and retractions, and thus to exert forces on their surroundings. Through experiments and modeling, I demonstrated that pilus interactions produce motility gradients in microcolonies potentially establishing a force gradient across the microcolonies. I was interested in testing the biological implications of those motility and force gradients, so I utilized an established genetic mutant, ∆pilT, which lacks the pilus retraction motor pilT (Merz, So, and Sheetz 2000). A ∆pilT mutant allowed us to measure physiological response in cells that do not produce retractive force from its pilus. I measured the level of gene expression of seven pilus-related genes in two backgrounds: WT and a pilus retraction-deficient mutant, ∆pilT. I found that some WT microcolonies express pilus-related genes in a heterogeneous fashion, while others are homogeneous. Spatiotemporal patterns in the microcolony are modified in a ∆pilT background. The presence or absence of retraction forces between bacteria have a profound impact on bacterial physiology: the WT and ∆pilT background do not survive in a classical static biofilm assay at the same rate. Together these results point toward a fundamental role for intracellular forces in shaping bacteria physiology. The work of biologists has been dominated by a biochemical perspective. Although biochemical processes, like metabolism and information transfer, are certainly essential in all hierarchical levels of life, there is growing evidence that physical forces may provide an alternate physiological mechanism. The introduction in Chapter 1 provides context for understanding the role of force pattern formation in multicellular structures, in the hopes to extend this line of thinking to microbial communities. The development of microbial communities relies on self-assembly of single cells. The development of Neisseria gonorrhoeae cellular aggregates rely exclusively on type IV pili interactions (Taktikos et al. 2015a). In Chapter 2 is a transcription of the publication where I explore the dynamics of the microcolonies (W. Pönisch et al. 2018a). We found that cells have differential motility depending where in the microcolony cells are located. Differential motility is a result of fewer pili-pili interactions on the perimeter of the microcolony, and more pili-pili interactions closer to the center. Therefore, due to frequency of pili-pili interactions, a gradient of motility produces heterogeneous behavior in the microcolony. To investigate whether heterogenous behavior is extended beyond motility, I investigated whether there is a connection between retraction force and the physiology of microcolonies. In Chapter 3 I used a quantitative approach to analyze seven pilus-related genes using fluorescent reporters. Using fluorescence and confocal microscopy, I quantified fluorescence intensity within space and time in microcolonies. Here, I provide evidence that physical intracellular cues in a three-dimensional bacterial aggregate provide context for spatial organization, since spatiotemporal patterning and survival in ∆pilT background are compromised in comparison to WT microcolonies. This suggests the important role PilT retraction force plays in regulating spatiotemporal patterning during early biofilm development. Lastly, in Chapter 4 I characterized some physical features of microcolonies. I measured the formation size and survival rates of microcolonies when exposed to a range of osmotic pressures. These experiments were motivated by my interest in understanding the native context of developing microcolonies. Microcolonies inhabit the viscous mucosal membranes of epithelial cells; therefore, I measured one aspect of the environmental effects of microcolony when exposed to similar osmotic pressure created by mucus. I also measured the plasticity of WT and ∆pilT microcolonies through squeezing microplate experiments. The overall aim of this work is to understand the role of physical force on microbial development. I largely focused on role of tfp forces on Neisseria gonorrhoeae microcolony formation. Characterizing gene expression in microcolonies provided key evidence for spatiotemporal heterogeneity in developing WT microcolonies. Heterogeneity was minimized without pilus retraction forces, which suggests that retraction forces play a role in the early development of biofilm formation

Pili mediated intercellular forces shape heterogeneous bacterial microcolonies prior to multicellular differentiation

Microcolonies are aggregates of a few dozen to a few thousand cells exhibited by many bacteria. The formation of microcolonies is a crucial step towards the formation of more mature bacterial communities known as biofilms, but also marks a significant change in bacterial physiology. Within a microcolony, bacteria forgo a single cell lifestyle for a communal lifestyle hallmarked by high cell density and physical interactions between cells potentially altering their behaviour. It is thus crucial to understand how initially identical single cells start to behave differently while assembling in these tight communities. Here we show that cells in the microcolonies formed by the human pathogen Neisseria gonorrhoeae (Ng) present differential motility behaviors within an hour upon colony formation. Observation of merging microcolonies and tracking of single cells within microcolonies reveal a heterogeneous motility behavior: cells close to the surface of the microcolony exhibit a much higher motility compared to cells towards the center. Numerical simulations of a biophysical model for the microcolonies at the single cell level suggest that the emergence of differential behavior within a multicellular microcolony of otherwise identical cells is of mechanical origin. It could suggest a route toward further bacterial differentiation and ultimately mature biofilms.Comment: 29 pages, 5 figures, supplementary information attache

Dissecting Sources of Quantitative Gene Expression Pattern Divergence Between Drosophila Species

The function of a transcriptional circuit is compared in three closely related species of Drosophila. Using quantitative imaging of gene expression, targeted transgenic reporter fly lines, and a computational framework, the sources of their differing expression outputs are identified

Strengthening The Organization and Reporting of Microbiome Studies (STORMS): A Reporting Checklist for Human Microbiome Research

Background Human microbiome research is a growing field with the potential for improving our understanding and treatment of diseases and other conditions. The field is interdisciplinary, making concise organization and reporting of results across different styles of epidemiology, biology, bioinformatics, translational medicine, and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Methods A multidisciplinary group of microbiome epidemiology researchers reviewed elements of available reporting guidelines for observational and genetic studies and adapted these for application to culture-independent human microbiome studies. New reporting elements were developed for laboratory, bioinformatic, and statistical analyses tailored to microbiome studies, and other parts of these checklists were streamlined to keep reporting manageable. Results STORMS is a 17-item checklist for reporting on human microbiome studies, organized into six sections covering typical sections of a scientific publication, presented as a table with space for author-provided details and intended for inclusion in supplementary materials. Conclusions STORMS provides guidance for authors and standardization for interdisciplinary microbiome studies, facilitating complete and concise reporting and augments information extraction for downstream applications. Availability The STORMS checklist is available as a versioned spreadsheet from https://www.stormsmicrobiome.org/

A Conserved Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila

Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells

Quantitative comparison of the anterior-posterior patterning system in the embryos of fiveDrosophilaspecies

Complex spatiotemporal gene expression patterns direct the development of the fertilized egg into an adult animal. Comparisons across species show that, in spite of changes in the underlying regulatory DNA sequence, developmental programs can be maintained across millions of years of evolution. Reciprocally, changes in gene expression can be used to generate morphological novelty. Distinguishing between changes in regulatory DNA that lead to changes in gene expression and those that do not is therefore a central goal of evolutionary developmental biology. Quantitative, spatially-resolved measurements of developmental gene expression patterns play a crucial role in this goal, enabling the detection of subtle phenotypic differences between species and the development of computations models that link the sequence of regulatory DNA to expression patterns. Here we report the generation of two atlases of cellular resolution gene expression measurements for the primary anterior-posterior patterning genes in Drosophila simulans and Drosophila virilis . By combining these data sets with existing atlases for three other Drosophila species, we detect subtle differences in the gene expression patterns and dynamics driving the highly conserved axis patterning system and delineate inter-species differences in the embryonic morphology. These data sets will be a resource for future modeling studies of the evolution of developmental gene regulatory networks

Dissecting sources of quantitative gene expression pattern divergence between Drosophila species.

Gene expression patterns can diverge between species due to changes in a gene's regulatory DNA or changes in the proteins, e.g., transcription factors (TFs), that regulate the gene. We developed a modeling framework to uncover the sources of expression differences in blastoderm embryos of three Drosophila species, focusing on the regulatory circuit controlling expression of the hunchback (hb) posterior stripe. Using this framework and cellular-resolution expression measurements of hb and its regulating TFs, we found that changes in the expression patterns of hb's TFs account for much of the expression divergence. We confirmed our predictions using transgenic D. melanogaster lines, which demonstrate that this set of orthologous cis-regulatory elements (CREs) direct similar, but not identical, expression patterns. We related expression pattern differences to sequence changes in the CRE using a calculation of the CRE's TF binding site content. By applying this calculation in both the transgenic and endogenous contexts, we found that changes in binding site content affect sensitivity to regulating TFs and that compensatory evolution may occur in circuit components other than the CRE

Quantitative Measurement and Thermodynamic Modeling of Fused Enhancers Support a Two-Tiered Mechanism for Interpreting Regulatory DNA.

Computational models of enhancer function generally assume that transcription factors (TFs) exert their regulatory effects independently, modeling an enhancer as a "bag of sites." These models fail on endogenous loci that harbor multiple enhancers, and a "two-tier" model appears better suited: in each enhancer TFs work independently, and the total expression is a weighted sum of their expression readouts. Here, we test these two opposing views on how cis-regulatory information is integrated. We fused two Drosophila blastoderm enhancers, measured their readouts, and applied the above two models to these data. The two-tier mechanism better fits these readouts, suggesting that these fused enhancers comprise multiple independent modules, despite having sequence characteristics typical of single enhancers. We show that short-range TF-TF interactions are not sufficient to designate such modules, suggesting unknown underlying mechanisms. Our results underscore that mechanisms of how modules are defined and how their outputs are combined remain to be elucidated