Agent-Based Modeling Demonstrates How Local Chemotactic Behavior Can Shape Biofilm Architecture.

Bacteria are often found living in aggregated multicellular communities known as biofilms. Biofilms are three-dimensional structures that confer distinct physical and biological properties to the collective of cells living within them. We used agent-based modeling to explore whether local cellular interactions were sufficient to give rise to global structural features of biofilms. Specifically, we asked whether chemorepulsion from a self-produced quorum-sensing molecule, autoinducer-2 (AI-2), was sufficient to recapitulate biofilm growth and cellular organization observed for biofilms of Helicobacter pylori, a common bacterial resident of human stomachs. To carry out this modeling, we modified an existing platform, Individual-based Dynamics of Microbial Communities Simulator (iDynoMiCS), to incorporate three-dimensional chemotaxis, planktonic cells that could join or leave the biofilm structure, and cellular production of AI-2. We simulated biofilm growth of previously characterized H. pylori strains with various AI-2 production and sensing capacities. Using biologically plausible parameters, we were able to recapitulate both the variation in biofilm mass and cellular distributions observed with these strains. Specifically, the strains that were competent to chemotax away from AI-2 produced smaller and more heterogeneously spaced biofilms, whereas the AI-2 chemotaxis-defective strains produced larger and more homogeneously spaced biofilms. The model also provided new insights into the cellular demographics contributing to the biofilm patterning of each strain. Our analysis supports the idea that cellular interactions at small spatial and temporal scales are sufficient to give rise to larger-scale emergent properties of biofilms.IMPORTANCE Most bacteria exist in aggregated, three-dimensional structures called biofilms. Although biofilms play important ecological roles in natural and engineered settings, they can also pose societal problems, for example, when they grow in plumbing systems or on medical implants. Understanding the processes that promote the growth and disassembly of biofilms could lead to better strategies to manage these structures. We had previously shown that Helicobacter pylori bacteria are repulsed by high concentrations of a self-produced molecule, AI-2, and that H. pylori mutants deficient in AI-2 sensing form larger and more homogeneously spaced biofilms. Here, we used computer simulations of biofilm formation to show that local H. pylori behavior of repulsion from high AI-2 could explain the overall architecture of H. pylori biofilms. Our findings demonstrate that it is possible to change global biofilm organization by manipulating local cell behaviors, which suggests that simple strategies targeting cells at local scales could be useful for controlling biofilms in industrial and medical settings.

Automated identification of conserved synteny after whole-genome duplication.

An important objective for inferring the evolutionary history of gene families is the determination of orthologies and paralogies. Lineage-specific paralog loss following whole-genome duplication events can cause anciently related homologs to appear in some assays as orthologs. Conserved synteny-the tendency of neighboring genes to retain their relative positions and orders on chromosomes over evolutionary time-can help resolve such errors. Several previous studies examined genome-wide syntenic conservation to infer the contents of ancestral chromosomes and provided insights into the architecture of ancestral genomes, but did not provide methods or tools applicable to the study of the evolution of individual gene families. We developed an automated system to identify conserved syntenic regions in a primary genome using as outgroup a genome that diverged from the investigated lineage before a whole-genome duplication event. The product of this automated analysis, the Synteny Database, allows a user to examine fully or partially assembled genomes. The Synteny Database is optimized for the investigation of individual gene families in multiple lineages and can detect chromosomal inversions and translocations as well as ohnologs (paralogs derived by whole-genome duplication) gone missing. To demonstrate the utility of the system, we present a case study of gene family evolution, investigating the ARNTL gene family in the genomes of Ciona intestinalis, amphioxus, zebrafish, and human.

Inferring ancestral gene order.

To explain the evolutionary mechanisms by which populations of organisms change over time, it is necessary to first understand the pathways by which genomes have changed over time. Understanding genome evolution requires comparing modern genomes with ancestral genomes, which thus necessitates the reconstruction of those ancestral genomes. This chapter describes automated approaches to infer the nature of ancestral genomes from modern sequenced genomes. Because several rounds of whole genome duplication have punctuated the evolution of animals with backbones, and current methods for ortholog calling do not adequately account for such events, we developed ways to infer the nature of ancestral chromosomes after genome duplication. We apply this method here to reconstruct the ancestors of a specific chromosome in the zebrafish Danio rerio.

Anticodon-dependent conservation of bacterial tRNA gene sequences.

The residues in tRNA that account for its tertiary fold and for its specific aminoacylation are well understood. In contrast, relatively little is known about the residues in tRNA that dictate its ability to transit the different sites of the ribosome. Yet protein synthesis cannot occur unless tRNA properly engages with the ribosome. This study analyzes tRNA gene sequences from 145 fully sequenced bacterial genomes. Grouping the sequences according to the anticodon triplet reveals that many residues in tRNA, including some that are distal to the anticodon loop, are conserved in an anticodon-dependent manner. These residues evade detection when tRNA genes are grouped according to amino acid family. The conserved residues include those at positions 32, 38, and 37 of the anticodon loop, which are already known to influence tRNA translational performance. Therefore, it seems likely that the newly detected anticodon-associated residues also influence tRNA performance on the ribosome. Remarkably, tRNA genes that belong to the same amino acid family and therefore share identical residues at the second and third anticodon positions have diverged, during bacterial evolution, into highly conserved groups that are defined by the residue at the first (wobble) anticodon position. Current ideas about the properties of tRNA and the translation mechanism do not fully account for this phenomenon. The results of the present study provide a foundation for studying the adaptation of individual tRNAs to the translation machinery and for future studies of the translation mechanism.

Aligning sequences by minimum description length.

This paper presents a new information theoretic framework for aligning sequences in bioinformatics. A transmitter compresses a set of sequences by constructing a regular expression that describes the regions of similarity in the sequences. To retrieve the original set of sequences, a receiver generates all strings that match the expression. An alignment algorithm uses minimum description length to encode and explore alternative expressions; the expression with the shortest encoding provides the best overall alignment. When two substrings contain letters that are similar according to a substitution matrix, a code length function based on conditional probabilities defined by the matrix will encode the substrings with fewer bits. In one experiment, alignments produced with this new method were found to be comparable to alignments from CLUSTALW. A second experiment measured the accuracy of the new method on pairwise alignments of sequences from the BAliBASE alignment benchmark.

A neural network model of chemotaxis predicts functions of synaptic connections in the nematode Caenorhabditis elegans.

The anatomical connectivity of the nervous system of the nematode Caenorhabditis elegans has been almost completely described, but determination of the neurophysiological basis of behavior in this system is just beginning. Here we used an optimization algorithm to search for patterns of connectivity sufficient to compute the sensorimotor transformation underlying C. elegans chemotaxis, a simple form of spatial orientation behavior in which turning probability is modulated by the rate of change of chemical concentration. Optimization produced differentiator networks capable of simulating chemotaxis. A surprising feature of these networks was inhibitory feedback connections on all neurons. Further analysis showed that feedback regulates the latency between sensory input and behavior. Common patterns of connectivity between the model and biological networks suggest new functions for previously identified connections in the C. elegans nervous system.

The origins of genome complexity.

Complete genomic sequences from diverse phylogenetic lineages reveal notable increases in genome complexity from prokaryotes to multicellular eukaryotes. The changes include gradual increases in gene number, resulting from the retention of duplicate genes, and more abrupt increases in the abundance of spliceosomal introns and mobile genetic elements. We argue that many of these modifications emerged passively in response to the long-term population-size reductions that accompanied increases in organism size. According to this model, much of the restructuring of eukaryotic genomes was initiated by nonadaptive processes, and this in turn provided novel substrates for the secondary evolution of phenotypic complexity by natural selection. The enormous long-term effective population sizes of prokaryotes may impose a substantial barrier to the evolution of complex genomes and morphologies.

The evolutionary demography of duplicate genes.

Although gene duplication has generally been viewed as a necessary source of material for the origin of evolutionary novelties, the rates of origin, loss, and preservation of gene duplicates are not well understood. Applying steady-state demographic techniques to the age distributions of duplicate genes censused in seven completely sequenced genomes, we estimate the average rate of duplication of a eukaryotic gene to be on the order of 0.01/ gene/million years, which is of the same order of magnitude as the mutation rate per nucleotide site. However, the average half-life of duplicate genes is relatively small, on the order of 4.0 million years. Significant interspecific variation in these rates appears to be responsible for differences in species-specific genome sizes that arise as a consequence of a quasi-equilibrium birth-death process. Most duplicated genes experience a brief period of relaxed selection early in their history and a minority exhibit the signature of directional selection, but those that survive more than a few million years eventually experience strong purifying selection. Thus, although most theoretical work on the gene-duplication process has focused on issues related to adaptive evolution, the origin of a new function appears to be a very rare fate for a duplicate gene. A more significant role of the duplication process may be the generation of microchromosomal rearrangements through reciprocal silencing of alternative copies, which can lead to the passive origin of post-zygotic reproductive barriers in descendant lineages of incipient species.

MUTATIONAL MELTDOWNS IN SEXUAL POPULATIONS.

Although it is widely acknowledged that the gradual accumulation of mildly deleterious mutations is an important source of extinction for asexual populations, it is generally assumed that this process is of little relevance to sexual species. Here we present results, based on computer simulations and supported by analytical approximations, that indicate that mutation accumulation in small, random-mating monoecious populations can lead to mean extinction times less than a few hundred to a few thousand generations. Unlike the situation in obligate asexuals in which the mean time to extinction (t̄e ) increases more slowly than linearly with the population carrying capacity (K), t̄e increases approximately exponentially with K in outcrossing sexual populations. The mean time to extinction for obligately selfing populations is shown to be equivalent to that for asexual populations of the same size, but with half the mutation rate and twice the mutational effect; this suggests that obligate selfing, like obligate asexuality, is inviable as a long-term reproductive strategy. Under all mating systems, the mean time to extinction increases relatively slowly with the logarithm of fecundity, and mutations with intermediate effects (similar to those observed empirically) cause the greatest risk of extinction. Because our analyses ignore sources of demographic and environmental stochasticity, which have synergistic effects that exacerbate the accumulation of deleterious mutations, our results should yield liberal upper bounds to the mean time to extinction caused by mutational degradation. Thus, deleterious mutation accumulation cannot be ruled out generally as a significant source of extinction vulnerability in small sexual populations or as a selective force influencing mating-system evolution.