On the role of metaheuristic optimization in bioinformatics

Metaheuristic algorithms are employed to solve complex and large-scale optimization problems in many different fields, from transportation and smart cities to finance. This paper discusses how metaheuristic algorithms are being applied to solve different optimization problems in the area of bioinformatics. While the text provides references to many optimization problems in the area, it focuses on those that have attracted more interest from the optimization community. Among the problems analyzed, the paper discusses in more detail the molecular docking problem, the protein structure prediction, phylogenetic inference, and different string problems. In addition, references to other relevant optimization problems are also given, including those related to medical imaging or gene selection for classification. From the previous analysis, the paper generates insights on research opportunities for the Operations Research and Computer Science communities in the field of bioinformatics

A Probabilistic Multi-Objective Artificial Bee Colony Algorithm for Gene Selection

Microarray technology is widely used to report gene expression data. The inclusion of many features and few samples is one of the characteristic features of this platform. In order to define significant genes for a particular disease, the problem of high-dimensionality microarray data should be overcome. The Artificial Bee Colony (ABC) Algorithm is a successful meta-heuristic algorithm that solves optimization problems effectively. In this paper, we propose a hybrid gene selection method for discriminatively selecting genes. We propose a new probabilistic binary Artificial Bee Colony Algorithm, namely PrBABC, that is hybridized with three different filter methods. The proposed method is applied to nine microarray datasets in order to detect distinctive genes for classifying cancer data. Results are compared with other wellknown meta-heuristic algorithms: Binary Differential Evolution Algorithm (BinDE), Binary Particle Swarm Optimization Algorithm (BinPSO), and Genetic Algorithm (GA), as well as with other methods in the literature. Experimental results show that the probabilistic self-adaptive learning strategy integrated into the employed-bee phase can boost classification accuracy with a minimal number of genes

Characterizing the fitness landscapes of gut symbionts in defined community and diet contexts

A species\u27 niche is the description of all the environmental conditions required to permit a population of that species to persist, including the effects of the population on those conditions. This definition includes the species\u27 resource requirements, as well as stress tolerances and interactions with other species acting as competitors, predators, parasites, and mutualists. The human gut microbiota serves as a microbial `metabolic organ\u27 tasked in part with the biotransformation of many components of our diet. Relatively little is known about the factors that allow members of the human gut microbiota to persist in a habitat that experiences marked changes in its nutrient environment. Identification of these factors is important for understanding the mechanisms that determine community assembly, community responses to and recovery after various perturbations, and the food webs that link microbes to one another and to their host. Therefore, in my thesis, I developed an experimental and computational pipeline for multi-taxon insertion sequencing (multi-taxon INSeq) to identify fitness determinants in multiple species and strains of human gut Bacteroides. Libraries of tens of thousands of transposon (Tn) mutants for each of four human gut Bacteroides strains, two of which represented the same species, were generated. These libraries were then introduced into adult germ-free mice as part of a 15-member artificial defined human gut microbiota containing 11 other wild-type bacterial species. Mice were fed diets either low in fat and high in plant polysaccharides (LF/HPP), or high in fat and simple sugars (HF/HS). Fecal samples, collected over time, were subjected to multi-taxon INSeq and my analysis pipeline, which was based on maximum likelihood estimation. A total of 86 core fitness determinants were identified across all four strains; a large fraction of these determinants were involved in various aspects of amino acid biosynthesis. Significant intra-species differences were detected in response to diet between two strains of Bacteroides thetaiotaomicron, highlighting differential strategies facilitating their co-existence within a complex community. By combining information gleaned from in vivo and in vitro INSeq experiments, as well as from in vivo and in vitro microbial RNA-Seq, I determined that arabinoxylan, the most common hemicellulose in cereals, was able to drive expression of a polysaccharide utilization locus that represented a key fitness factor in Bacteroides cellulosilyticus WH2 when mice consumed HF/HS diet. Supplementation of the drinking water with this glycan in turn significantly increased the representation of B. cellulosilyticus WH2 within the defined community in the context of the high fat diet. Multi-taxon INSeq defined the changes in fitness determinants of this and the other Bacteroides in response to arabinoxylan supplementation. Collectively, these studies revealed multiple mechanisms by which our microbial symbionts establish themselves in the gut, including species-specific, strain-specific, as well as core responses, which mapped to a variety of metabolic/nutrient processing pathways. The approach described for mapping fitness landscapes in a community context should facilitate discovery efforts aimed at identifying the niches of microbiota members, as well as ways to deliberately reshape community structure and function through dietary interventions

Effects of diet on resource utilization by a model human gut microbiota containing Bacteroides cellulosilyticus WH2, a symbiont with an extensive glycobiome

The human gut microbiota is an important metabolic organ, yet little is known about how its individual species interact, establish dominant positions, and respond to changes in environmental factors such as diet. In this study, gnotobiotic mice were colonized with an artificial microbiota comprising 12 sequenced human gut bacterial species and fed oscillating diets of disparate composition. Rapid, reproducible, and reversible changes in the structure of this assemblage were observed. Time-series microbial RNA-Seq analyses revealed staggered functional responses to diet shifts throughout the assemblage that were heavily focused on carbohydrate and amino acid metabolism. High-resolution shotgun metaproteomics confirmed many of these responses at a protein level. One member, Bacteroides cellulosilyticus WH2, proved exceptionally fit regardless of diet. Its genome encoded more carbohydrate active enzymes than any previously sequenced member of the Bacteroidetes. Transcriptional profiling indicated that B. cellulosilyticus WH2 is an adaptive forager that tailors its versatile carbohydrate utilization strategy to available dietary polysaccharides, with a strong emphasis on plant-derived xylans abundant in dietary staples like cereal grains. Two highly expressed, diet-specific polysaccharide utilization loci (PULs) in B. cellulosilyticus WH2 were identified, one with characteristics of xylan utilization systems. Introduction of a B. cellulosilyticus WH2 library comprising >90,000 isogenic transposon mutants into gnotobiotic mice, along with the other artificial community members, confirmed that these loci represent critical diet-specific fitness determinants. Carbohydrates that trigger dramatic increases in expression of these two loci and many of the organism's 111 other predicted PULs were identified by RNA-Seq during in vitro growth on 31 distinct carbohydrate substrates, allowing us to better interpret in vivo RNA-Seq and proteomics data. These results offer insight into how gut microbes adapt to dietary perturbations at both a community level and from the perspective of a well-adapted symbiont with exceptional saccharolytic capabilities, and illustrate the value of artificial communities

Diet related adaptations across a small mammal hybrid zone

Hybrid zones have long been used to investigate divergence and speciation. Many hybrid zones occur across sharp ecotones—areas characterized by transition in biological community composition. Such hybrid zones are often the result of secondary contact—when populations that descended from a common ancestral population come into contact after a period of allopatry. These populations may have accumulated differences via neutral process (i.e., genetic drift) or adaptation to differing environments. In the absence of complete reproductive isolation, genes may then flow between these differentially adapted populations. Vegetation turnover is common across ecotones, and plant availability is important to mammalian herbivores that consume plants that often produce toxic plant secondary compounds (PSCs). Availability of diet plants for which mammalian herbivores are adapted may limit movement and underlie pre- and post-zygotic isolating mechanisms across sharp ecotones. I studied diet and diet-related adaptions in a mammalian hybrid zone between two species of woodrat (Neotoma) that occurs across a sharp ecotone characterized by differences in plant community composition. Using live-trapping and field-based experiments, coupled with amplicon sequencing of DNA extracted from woodrat feces, I quantified variation in diet, diet preference, and gut microbiome composition between N. lepida (desert woodrat) and N. bryanti (Bryant’s woodrat), and F1 and backcross hybrids. I found that each parental species maintains distinct diets that contain plants that produce toxic PSCs but these plants were also among the most nutritional across the site. Furthermore, these dietary differences were maintained across seasons and years that spanned more wet to more dry periods. These diets were also associated with differences in microbiome composition, and while diet was primarily predicted by habitat, microbiome composition was constrained by genotype. I then used laboratory-based feeding experiments to determine how each species responds—physiologically, genetically, and behaviorally—to their native and non-native diet. Diet experiments were followed with 16S rRNA sequencing of contents from woodrat caecum, as well as RNA sequencing of tissue from the liver and caecum of woodrats. Response to diet treatments was asymmetrical, with N. lepida exhibiting greater response behaviorally, genetically, and in gut microbiome composition. Gene expression in liver was strongly influenced by species and exhibited little effect of diet treatment, but differential expression of genes in the caecum exhibited strong species by diet interaction effects. Neotoma lepida exhibited a strong diet effect in genes expressed in the caecum, as well as in differences in microbiota of the caecum. These results suggest that interactions between host genes and microbes contained in the caecum may play a role in the metabolism of plant PSCs. These field-based observations and laboratory-based experiments add to our understanding of how diet and diet-related adaptations may influence gene flow across this small mammal hybrid zone

The role of RFX transcription factors in neurons and in the human brain

RFX transcription factors (TFs) are conserved in animals, fungi and some amoebae, but not in algae, plants and protozoan species. The conservation is based on the protein sequence of the DNA binding domain (DBD). The RFX DBD recognizes and binds to a DNA sequence motif called the X-box. In addition to the DBD, most RFX TFs have a Dimerization domain (DIM). The DIM enables RFX TFs to form homo- or heterodimers in detecting the X-box motif, rendering the X-box often described as an imperfect palindromic sequence of two 6-bp half-sites with variable spacers. So far, RFX TFs are known to regulate gene transcription in cell cycle, DNA repair, immune response, collagen transcription, insulin production, spermatogenesis and hearing. In animals, the most common feature of RFX TFs is their regulation of ciliogenesis and the maintenance of specialized functions of ciliated cells. Cilia are hair-like cell protrusions. They are present in all animals but absent in many species of fungi, amoebae and flowering plants. Based on the inner structure, cilia can be divided into two types, the primary cilia (one cilium per cell) and the motile cilia (either as mono-cilia or multiple-cilia per cell). The primary cilia are less understood despite being present on nearly every cell in the human body. Humans have eight RFX genes (RFX1-8) which are expressed in diverse tissues and cell types. This thesis serves to expand knowledge of the RFX TF family in humans and their role in primary cilia and neurons, with interest in human brain development and function. We used databases (Paper I), human cell lines (Papers I and II) and the worm C. elegans (Paper III) as our materials for experimentation. In Paper I, we performed an extensive survey of RFX1-8 expression by transcription start site (TSS) counts from the FANTOM5 database. RFX1-4 and RFX7 are prominently expressed in different brain tissues and spinal cord, making them the reference RFX TFs for neurons and the human brain. Furthermore, we predicted the regulation preference of RFX TFs based on co-clustering expression analysis with known RFX target genes. We also analyzed the positioning of the X-box motifs in the human genome and uncovered potential upstream regulators of RFX genes. In Paper II, we explored the role of RFX TFs in the context of developmental dyslexia, a developmental disorder of the human brain. The dyslexia candidate genes DYX1C1, DCDC2 and KIAA0319 have functional X-box motifs in their promoter regions, as shown by luciferase reporter assay of wild-type versus mutated X-boxes. By siRNA knockdowns of RFX1-3, we showed a complex regulatory mechanism among RFX1-3 in regulating DYX1C1 and DCDC2. Additionally, both DYX1C1 and DCDC2 localize to the primary cilia. In Paper III, we performed microarray analysis of target genes of DAF-19, the sole RFX TF of C. elegans, at three developmental stages (3-fold embryo, L1-larvae and adult). At all stages, DAF-19-regulated target genes were significantly enriched in neurons. Using transcriptional GFP reporter constructs, we observed that DAF-19-dependent target genes (both activated and repressed) affected only neurons, both ciliated and non-ciliated. Altogether, we provided insight into the role of RFX TFs for primary cilia and neurons. We speculate that RFX TFs and primary cilia continue to play a defined role for mature neuron function in the human brain

Epigenetic marks of a stable host-microbiota association in the mammalian gut

To summarize, the results shown here confirms that the host-microbiota interaction is a critical check pint for intestinal inflammation and development. Though, it is still a debate whether the interaction is a cause or consequence of the disease, the results indicate a potential role of epigenetic modification in disease manifestation of UC or postnatal development. The finding might be helpful to support the combinational epigenetic and microbiota based therapies of intestine inflammation

Transcriptional effects of predator cues in the brain of Spodoptera frugiperda (lepidoptera: noctuidae) moths exposed to bat ultrasound

Exposure to predators induces broad behavioral and physiological responses that have traditionally been considered acute and transitory. However, prolonged frequent exposure to predators and the chemical, visual, tactile, and auditory cues they broadcast to the environment are now known to have long-term impacts on prey physiology and life-histories. Knowledge on the molecular mechanisms responsible for inducing both acute and chronic responses to predator exposure is limited. Although several studies have assessed acute and chronic stress responses in a variety of taxa, these efforts have often involved a priori expectations of the molecular pathways involved in the physiological response, such as glucocorticoid and neurohormone production. While relatively little is known about physiological and molecular predator-induced stress responses in insects, many dramatic defensive behaviors in insects have been reported. Within several moth families, such as Noctuidae, tympanic organs for recognizing ultrasonic bat calls have evolved and facilitate the avoidance of predation via eliciting flight cessation or aerial maneuvers when stimulated by ultrasound. In this study, I exposed adult male fall armyworm (Spodoptera frugiperda) moths to recorded ultrasonic bat foraging and attack calls for a prolonged period and constructed a de novo transcriptome using RNA-Seq on mRNA extracted from the brains of predator-exposed and unexposed moths. I then identified differentially-expressed transcripts between the exposed and control groups and used functional gene analysis and Gene Ontology (GO) enrichment analysis to reveal that the majority of differentially expressed transcripts corresponded to a broad range of proteins involved in cellular processes in the brain, including glutamate production and metabolism, ionotropic sensory receptor expression, mitochondrial metabolism, actin cytoskeleton dynamics, chromatin binding and other epigenetic modifications, axonal guidance and remodeling, cilia function and development, Wnt signaling, and TOR signaling. The top five significantly over-represented GO terms included chromatin binding, macromolecular complex binding, glutamate synthase activity, glutamate metabolic process, and glutamate biosynthetic process. Although limited by a de novo approach, this study demonstrates that predator-induced transcriptional responses in S. frugiperda vary broadly in their physiological and molecular functions. As a first assessment of auditory predator cues on transcriptional responses in moth prey, this study also lays the foundation for future research on the complex array of integrated behavioral, physiological, and cellular responses to predators observed in ultrasound-sensitive Lepidoptera