Tumor­suppressive effects of Smad­ubiquitination regulator 2 in papillary thyroid carcinoma.

Smad-ubiquitination regulator 2 (SMURF2) functions as a homolog of E6AP carboxyl terminus-type E3 ubiquitin ligase to regulate cell cycle progression and tumor growth factor expression. SMURF2 has been revealed to function as a tumor suppressor in a number of cancers; however, its function in papillary thyroid carcinoma (PTC) remains largely unknown. Therefore, the aim of the present study was to investigate the function of SMURF2 in PTC. Reverse transcription-quantitative PCR and western blotting were used to detect cellular expression of SMURF2 in vitro. After increasing or inhibiting the expression of SMURF2, MTT was used to detect the effect on tumor cell proliferation and Transwell assays were used to detect the effect on tumor cell migration and invasion. Finally, ELISA was used to detect the effects on glucose and glutamine metabolism in tumor cells and the findings revealed that SMURF2 was downregulated in PTC tissues. Moreover, SMURF2 inhibited the proliferation, invasion and migration of PTC cells, and promoted their apoptosis. Finally, SMURF2 inhibited cell glycolysis and glutaminolysis and affected metabolism in the PTC cell line, TPC-1. Thus, the findings of the present study suggest that SMURF2 may be a potential target in the treatment of PTC.

A CANCER PERSISTENT DNA REPAIR CIRCUIT DRIVEN BY MDM2, MDM4 (MDMX), AND MUTANT P53 FOR RECRUITMENT OF MDC1 AND 53BP1 TO CHROMATIN.

The influence of the metastasis promoting proteins mutant p53 (mtp53) and MDM2 on Cancer Persistent Repair (CPR) to promote cancer cell survival is understudied. Interactions between the DNA repair choice protein 53BP1 and wild type tumor suppressor protein p53 (wtp53) regulates cell cycle control. Cancer cells often express elevated levels of transcriptionally inactive missense mutant p53 (mtp53) that interacts with MDM2 and MDM4/MDMX (herein called MDMX). The ability of mtp53 to maintain a 53BP1 interaction while in the context of interactions with MDM2 and MDMX has not been described. We asked if MDM2 regulates chromatin-based phosphorylation events in the context of mtp53 by comparing the chromatin of T47D breast cancer cells with and without MDM2 in a phospho-peptide stable isotope labeling in cell culture (SILAC) screen. We found reduced phospho-53BP1 chromatin association, which we confirmed by chromatin fractionation and immunofluorescence in multiple breast cancer cell lines. We used the Proximity Ligation Assay (PLA) in breast cancer cell lines and detected 53BP1 in close proximity to mtp53, MDM2, and the DNA repair protein MDC1. Through disruption of the mtp53-MDM2 interaction, by either Nutlin 3a or a mtp53 R273H C-terminal deletion, we uncovered that mtp53 was required for MDM2-53BP1 interaction foci. Our data suggests that mtp53 works with MDM2 and 53BP1 to promote CPR and cell survival.

Quantity of questing black-legged ticks and associated micro-scale environmental data collected from four Suburban Parks near New York City.

During 2017 and 2018, we collected the quantity of questing black-legged ticks (Ixodes scapularis), also known as deer ticks, in 124 sampling sites of 5m by 5m in four state parks-Caumsett State Historic Park, Connetquot River State Park, Rockefeller State Park, and Fire Island National Seashore-around New York City. The black-legged tick is the primary vector for the spirochete Borrelia burgdorferi, the pathogen of Lyme disease, in Northeastern United States. Using the flagging method, we collected and counted the numbers of adult and nymphal black-legged ticks at each stie. Along with these quantities, we also recorded the geographic coordinates, ambient temperature, and relative humidity at the sampling sites. Using high-resolution aerial imagery and LiDAR data, we further derived land cover composition, ecotone boundary length, normalized difference vegetation index (NDVI), elevation, solar radiation, and other environmental factors. The data could be used to conduct longitudinal analysis at the same sampling sites as well as comparison with other sites. Ecologists and environmental scientists can use the data for spatiotemporal and statistical analyses of tick ecology at the local scale.

Upregulation of ubiquitin carboxy­terminal hydrolase 47 (USP47) in papillary thyroid carcinoma ex vivo and reduction of tumor cell malignant behaviors after USP47 knockdown by stabilizing SATB1 expression in vitro.

Aberrant ubiquitination contributes to cancer development, including thyroid carcinoma. The present study assessed the expression of ubiquitin carboxy-terminal hydrolase 47 (USP47) and underlying molecular events in the development of papillary thyroid carcinoma (PTC). The effects of USP47 on PTC cell invasion and migration were analyzed by Transwell assays, while. the effects of USP47 and SATB1on PTC cell gene expression and changes in tumor cell metabolism were assayed by reverse transcription-quantitative PCR, western bolt, or ELISA, respectively. The expression of USP47 mRNA and protein was upregulated in PTC tissue and associated with the PTC tumor size. Knockdown of USP47 expression in PTC cell lines (TPC-1 and K1), decreased the cell proliferation mobility and invasion capacities, whereas USP47 overexpression in these cell lines showed an inverse effect and promoted cell glycolysis and glutamine metabolism. Moreover, expression of special AT-rich sequence-binding protein-1 (SATB1) was high in PTC tissue and was associated with USP47 expression. SATB1 expression promoted tumor cell glycolysis and glutamine metabolism, while USP47 protein bound to and deubiquitinated SATB1 to increase its intracellular levels, thus promoting glycolysis and glutamine metabolism. USP47 promotion of PTC development may be due to its stabilization of SATB1 protein, suggesting that targeting the USP47/SATB1 signaling axis may serve as a therapeutic intervention for PTC.

Novelty Search Promotes Antigenic Diversity in Microbial Pathogens.

Driven by host-pathogen coevolution, cell surface antigens are often the fastest evolving parts of a microbial pathogen. The persistent evolutionary impetus for novel antigen variants suggests the utility of novelty-seeking algorithms in predicting antigen diversification in microbial pathogens. In contrast to traditional genetic algorithms maximizing variant fitness, novelty-seeking algorithms optimize variant novelty. Here, we designed and implemented three evolutionary algorithms (fitness-seeking, novelty-seeking, and hybrid) and evaluated their performances in 10 simulated and 2 empirically derived antigen fitness landscapes. The hybrid walks combining fitness- and novelty-seeking strategies overcame the limitations of each algorithm alone, and consistently reached global fitness peaks. Thus, hybrid walks provide a model for microbial pathogens escaping host immunity without compromising variant fitness. Biological processes facilitating novelty-seeking evolution in natural pathogen populations include hypermutability, recombination, wide dispersal, and immune-compromised hosts. The high efficiency of the hybrid algorithm improves the evolutionary predictability of novel antigen variants. We propose the design of escape-proof vaccines based on high-fitness variants covering a majority of the basins of attraction on the fitness landscape representing all potential variants of a microbial antigen.

Genomic Confirmation of Borrelia garinii, United States.

Lyme disease is a multisystem disorder primarily caused by Borrelia burgdorferi sensu lato. However, B. garinii, which has been identified on islands off the coast of Newfoundland and Labrador, Canada, is a cause of Lyme disease in Eurasia. We report isolation and whole-genome nucleotide sequencing of a B. garinii isolate from a cotton mouse (Peromyscus gossypinus) in South Carolina, USA. We identified a second B. garinii isolate from the same repository. Phylogenetic analysis does not associate these isolates with the previously described isolates of B. garinii from Canada.

Evolution of the vls Antigenic Variability Locus of the Lyme Disease Pathogen and Development of Recombinant Monoclonal Antibodies Targeting Conserved VlsE Epitopes.

VlsE (variable major protein-like sequence, expressed) is an outer surface protein of the Lyme disease pathogen (Borreliella species) responsible for its within-host antigenic variation and a key diagnostic biomarker of Lyme disease. However, the high sequence variability of VlsE poses a challenge to the development of consistent VlsE-based diagnostics and therapeutics. In addition, the standard diagnostic protocols detect immunoglobins elicited by the Lyme pathogen, not the presence of the pathogen or its derived antigens. Here, we described the development of recombinant monoclonal antibodies (rMAbs) that bound specifically to conserved epitopes on VlsE. We first quantified amino-acid sequence variability encoded by the vls genes from 13 B. burgdorferi genomes by evolutionary analyses. We showed broad inconsistencies of the sequence phylogeny with the genome phylogeny, indicating rapid gene duplications, losses, and recombination at the vls locus. To identify conserved epitopes, we synthesized peptides representing five long conserved invariant regions (IRs) on VlsE. We tested the antigenicity of these five IR peptides using sera from three mammalian host species including human patients, the natural reservoir white-footed mouse (Peromyscus leucopus), and VlsE-immunized New Zealand rabbits (Oryctolagus cuniculus). The IR4 and IR6 peptides emerged as the most antigenic and reacted strongly with both the human and rabbit sera, while all IR peptides reacted poorly with sera from natural hosts. Four rMAbs binding specifically to the IR4 and IR6 peptides were identified, cloned, and purified. Given their specific recognition of the conserved epitopes on VlsE, these IR-specific rMAbs are potential novel diagnostic and research agents for direct detection of Lyme disease pathogens regardless of strain heterogeneity. IMPORTANCE Current diagnostic protocols of Lyme disease indirectly detect the presence of antibodies produced by the patient upon infection by the bacterial pathogen, not the pathogen itself. These diagnostic tests tend to underestimate early-stage bacterial infections before the patients develop robust immune responses. Further, the indirect tests do not distinguish between active or past infections by the Lyme disease bacteria in a patient sample. Here, we described novel monoclonal antibodies that have the potential to become the basis of direct and definitive diagnostic detection of the Lyme disease pathogen, regardless of its genetic heterogeneity.

Erratum to "A two-microRNA signature predicts the progression of male thyroid cancer".

[This corrects the article DOI: 10.1515/biol-2021-0099.].

ASF1B: A Possible Prognostic Marker, Therapeutic Target, and Predictor of Immunotherapy in Male Thyroid Carcinoma.

BACKGROUND: Thyroid carcinoma (TC) is the most common malignant endocrine tumor worldwide. Several studies have documented that male patients with TC have a higher rate of metastasis and disease recurrence than female patients. However, the mechanism underlying this observation is not completely clear. The goal of our research was to investigate the potential key candidate genes and pathways related to TC progression in male patients at the molecular level. METHODS: A total of 320 samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Hub genes were screened out using weighted gene coexpression network analysis (WGCNA) and a protein-protein interaction (PPI) network analysis. Survival analysis was used to identify hub genes associated with disease-free survival (DFS) rates. Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression (ESTIMATE) data were used to assess the relationship between hub genes and immune cell infiltration. The molecular mechanism and biological functions of hub genes were explored using RT-qPCR, Western blot, Cell Counting Kit-8 Assay, flow cytometry, Transwell assays, and scratch assays. RESULTS: Forty-seven hub genes were identified, and the survival analysis demonstrated that anti-silencing function 1B (ASF1B) was the sole independent risk factor for poor DFS in male TC patients. Possible associations between the results from the ESTIMATE analysis showed that the ASF1B expression level was related to the ESTIMATE score, immune score, and T-cell regulatory (Treg) infiltration level. Through in vitro cell function experiments, we verified that knockdown of ASF1B inhibited KTC-1 cell proliferation, promoted cell apoptosis, and blocked cell cycle. The silencing of ASF1B reduced protein kinase B (AKT), phospho-AKT (p-AKT), and forkhead box p3 (FOXP3) in KTC-1 cells. Moreover, FOXP3 overexpression markedly restored the cell migration, invasion, and proliferation abilities repressed by ASF1B knockdown. CONCLUSIONS: Our results indicate that ASF1B can be considered a prognostic marker, therapeutic target, and predictor of immunotherapy response in male thyroid cancer patients. However, further in-depth studies are required to validate this finding.

Maximum antigen diversification in a lyme bacterial population and evolutionary strategies to overcome pathogen diversity.

Natural populations of pathogens and their hosts are engaged in an arms race in which the pathogens diversify to escape host immunity while the hosts evolve novel immunity. This co-evolutionary process poses a fundamental challenge to the development of broadly effective vaccines and diagnostics against a diversifying pathogen. Based on surveys of natural allele frequencies and experimental immunization of mice, we show high antigenic specificities of natural variants of the outer surface protein C (OspC), a dominant antigen of a Lyme Disease-causing bacterium (Borrelia burgdorferi). To overcome the challenge of OspC antigenic diversity to clinical development of preventive measures, we implemented a number of evolution-informed strategies to broaden OspC antigenic reactivity. In particular, the centroid algorithm-a genetic algorithm to generate sequences that minimize amino-acid differences with natural variants-generated synthetic OspC analogs with the greatest promise as diagnostic and vaccine candidates against diverse Lyme pathogen strains co-existing in the Northeast United States. Mechanistically, we propose a model of maximum antigen diversification (MAD) mediated by amino-acid variations distributed across the hypervariable regions on the OspC molecule. Under the MAD hypothesis, evolutionary centroids display broad cross-reactivity by occupying the central void in the antigenic space excavated by diversifying natural variants. In contrast to vaccine designs based on concatenated epitopes, the evolutionary algorithms generate analogs of natural antigens and are automated. The novel centroid algorithm and the evolutionary antigen designs based on consensus and ancestral sequences have broad implications for combating diversifying pathogens driven by pathogen-host co-evolution.

A two-microRNA signature predicts the progression of male thyroid cancer.

In various cancers, microRNAs (miRNAs) are abnormally expressed, including thyroid cancer (TC). In recent years, the incidence of TC has increased annually around the world. Compared with female patients, male TC patients are more likely to have a postoperative recurrence and lymph node metastasis, and hence need second treatments. However, the molecular biological processes underlying this phenomenon are not understood. Therefore, we collected data on miRNA expression and clinical information of male TC patients from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs were identified between male TC tissues and matched normal tissues. The Kaplan-Meier method, univariate and multivariate Cox regressions, and receiver operating characteristic curve analyses were performed to assess the association between miRNAs and the disease-free survival of male TC patients. Gene Ontology (GO) and the Kyoto Encyclopaedia of Gene and Genome (KEGG) enrichment analyses were then used to explore the function of miRNA target genes. Furthermore, we evaluated the ability of the miRNA biomarker to predict survival in female TC patients. As a result, a total of 118 differentially expressed miRNAs were identified, including 25 upregulated and 93 downregulated miRNAs. Among them, miR-451a and miR-16-1-3p were confirmed to be independent prognostic factors for the disease-free survival rate. The target genes of miR-451a and miR-16-1-3p were identified, and functional analysis showed that these genes were enriched in 25 Go and KEGG accessions, including cell signal transduction, motor adhesion, phagocytosis, regulation of transcription, cell proliferation, angiogenesis, etc. Neither miR-451a and miR-16-1-3p, nor a prediction model based on both miRNAs effectively predicted survival in female TC patients. In conclusion, both miR-451a and miR-16-1-3p may play important roles in the processes of male TC. The two-miRNA signature involving miR-1258 and miR-193a may serve as a novel prognostic biomarker for male TC patients.

Multipartite Genome of Lyme Disease Borrelia: Structure, Variation and Prophages.

All members of the Borrelia genus that have been examined harbour a linear chromosome that is about 900 kbp in length, as well as a plethora of both linear and circular plasmids in the 5-220 kbp size range. Genome sequences for 27 Lyme disease Borrelia isolates have been determined since the elucidation of the B. burgdorferi B31 genome sequence in 1997. The chromosomes, which carry the vast majority of the housekeeping genes, appear to be very constant in gene content and organization across all Lyme disease Borrelia species. The content of the plasmids, which carry most of the genes that encode the differentially expressed surface proteins that interact with the spirochete's arthropod and vertebrate hosts, is much more variable. Lyme disease Borrelia isolates carry between 7-21 different plasmids, ranging in size from 5-84 kbp. All strains analyzed to date harbor three plasmids, cp26, lp54 and lp17. The plasmids are unusual, as compared to most bacterial plasmids, in that they contain many paralogous sequences, a large number of pseudogenes, and, in some cases, essential genes. In addition, a number of the plasmids have features indicating that they are prophages. Numerous methods have been developed for Lyme disease Borrelia strain typing. These have proven valuable for clinical and epidemiological studies, as well as phylogenomic and population genetic analyses. Increasingly, these approaches have been displaced by whole genome sequencing techniques. Some correlations between genome content and pathogenicity have been deduced, and comparative whole genome analyses promise future progress in this arena.

Population Differentiation at the PVT1 Gene Locus: Implications for Prostate Cancer.

Genetic variation in susceptibility to complex diseases, such as cancer, is well-established. Enrichment of disease associated alleles in specific populations could have implications for disease incidence and prevalence. Prostate cancer (PCa) is a disease with well-established higher incidence, prevalence, and worse outcomes among men of African ancestry in comparison to other populations. PCa is a multi-factorial, complex disease, but the exact mechanisms for its development and progression are unclear. The gene desert located on chromosome 8q24 is associated with aggressiveness of PCa. Interestingly, the non-protein coding gene locus Plasmacytoma Variant Translocation (PVT1) is present at chromosome 8q24 and is overexpressed in PCa. PVT1 gives rise to multiple transcripts with potentially different molecular and cellular functions. In an analysis of the PVT1 locus using data from the 1000 Genomes Project, we found the chromosomal region spanning PVT1 exons 4A and 4B to be highly differentiated between African and non-African populations. We further investigated levels of gene expression of PVT1 exons 4A and 4B and observed significant overexpression of these exons in PCa tissues relative to benign prostatic hyperplasia and to normal prostate tissues obtained from men of African ancestry. These results indicate that PVT1 exons 4A and 4B may have clinical implications in PCa a conclusion supported by the observation that transient and stable overexpression of PVT1 exons 4A and 4B significantly induce greater prostate epithelial cell migration and proliferation. We anticipate that further exploration of the role of PVT1 exons 4A and 4B may lead to the development of diagnostic, therapeutic, and other clinical applications in PCa.

Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection.

Pseudomonas aeruginosa, a main cause of human infection, can gain resistance to the antibiotic aztreonam through a mutation in NalD, a transcriptional repressor of cellular efflux. Here we combine computational analysis of clinical isolates, transcriptomics, metabolic modeling and experimental validation to find a strong association between NalD mutations and resistance to aztreonam-as well as resistance to other antibiotics-across P. aeruginosa isolated from different patients. A detailed analysis of one patient's timeline shows how this mutation can emerge in vivo and drive rapid evolution of resistance while the patient received cancer treatment, a bone marrow transplantation, and antibiotics up to the point of causing the patient's death. Transcriptomics analysis confirmed the primary mechanism of NalD action-a loss-of-function mutation that caused constitutive overexpression of the MexAB-OprM efflux system-which lead to aztreonam resistance but, surprisingly, had no fitness cost in the absence of the antibiotic. We constrained a genome-scale metabolic model using the transcriptomics data to investigate changes beyond the primary mechanism of resistance, including adaptations in major metabolic pathways and membrane transport concurrent with aztreonam resistance, which may explain the lack of a fitness cost. We propose that metabolic adaptations may allow resistance mutations to endure in the absence of antibiotics and could be targeted by future therapies against antibiotic resistant pathogens.

Genetic codes optimized as a traveling salesman problem.

The Standard Genetic Code (SGC) is robust to mutational errors such that frequently occurring mutations minimally alter the physio-chemistry of amino acids. The apparent correlation between the evolutionary distances among codons and the physio-chemical distances among their cognate amino acids suggests an early co-diversification between the codons and amino acids. Here we formulated the co-minimization of evolutionary distances between codons and physio-chemical distances between amino acids as a Traveling Salesman Problem (TSP) and solved it with a Hopfield neural network. In this unsupervised learning algorithm, macromolecules (e.g., tRNAs and aminoacyl-tRNA synthetases) associating codons with amino acids were considered biological analogs of Hopfield neurons associating "tour cities" with "tour positions". The Hopfield network efficiently yielded an abundance of genetic codes that were more error-minimizing than SGC and could thus be used to design artificial genetic codes. We further argue that as a self-optimization algorithm, the Hopfield neural network provides a model of origin of SGC and other adaptive molecular systems through evolutionary learning.

Analysis of a flagellar filament cap mutant reveals that HtrA serine protease degrades unfolded flagellin protein in the periplasm of Borrelia burgdorferi.

Unlike external flagellated bacteria, spirochetes have periplasmic flagella (PF). Very little is known about how PF are assembled within the periplasm of spirochaetal cells. Herein, we report that FliD (BB0149), a flagellar cap protein (also named hook-associated protein 2), controls flagellin stability and flagellar filament assembly in the Lyme disease spirochete Borrelia burgdorferi. Deletion of fliD leads to non-motile mutant cells that are unable to assemble flagellar filaments and pentagon-shaped caps (10 nm in diameter, 12 nm in length). Interestingly, FlaB, a major flagellin protein of B. burgdorferi, is degraded in the fliD mutant but not in other flagella-deficient mutants (i.e., in the hook, rod, or MS-ring). Biochemical and genetic studies reveal that HtrA, a serine protease of B. burgdorferi, controls FlaB turnover. Specifically, HtrA degrades unfolded but not polymerized FlaB, and deletion of htrA increases the level of FlaB in the fliD mutant. Collectively, we propose that the flagellar cap protein FliD promotes flagellin polymerization and filament growth in the periplasm. Deletion of fliD abolishes this process, which leads to leakage of unfolded FlaB proteins into the periplasm where they are degraded by HtrA, a protease that prevents accumulation of toxic products in the periplasm.

Genotyping and Quantifying Lyme Pathogen Strains by Deep Sequencing of the Outer Surface Protein C (ospC) Locus.

A mixed infection of a single tick or host by Lyme disease spirochetes is common and a unique challenge for the diagnosis, treatment, and surveillance of Lyme disease. Here, we describe a novel protocol for differentiating Lyme strains on the basis of deep sequencing of the hypervariable outer surface protein C locus (ospC). Improving upon the traditional DNA-DNA hybridization method, the next-generation sequencing-based protocol is high throughput, quantitative, and able to detect new pathogen strains. We applied the method to more than one hundred infected Ixodes scapularis ticks collected from New York State, USA, in 2015 and 2016. An analysis of strain distributions within individual ticks suggests an overabundance of multiple infections by five or more strains, inhibitory interactions among coinfecting strains, and the presence of a new strain closely related to Borreliella bissettiae A supporting bioinformatics pipeline has been developed. The newly designed pair of universal ospC primers target intergenic sequences conserved among all known Lyme pathogens. The protocol could be used for culture-free identification and quantification of Lyme pathogens in wildlife and potentially in clinical specimens.

BpWrapper: BioPerl-based sequence and tree utilities for rapid prototyping of bioinformatics pipelines.

BACKGROUND: Automated bioinformatics workflows are more robust, easier to maintain, and results more reproducible when built with command-line utilities than with custom-coded scripts. Command-line utilities further benefit by relieving bioinformatics developers to learn the use of, or to interact directly with, biological software libraries. There is however a lack of command-line utilities that leverage popular Open Source biological software toolkits such as BioPerl ( http://bioperl.org ) to make many of the well-designed, robust, and routinely used biological classes available for a wider base of end users. RESULTS: Designed as standard utilities for UNIX-family operating systems, BpWrapper makes functionality of some of the most popular BioPerl modules readily accessible on the command line to novice as well as to experienced bioinformatics practitioners. The initial release of BpWrapper includes four utilities with concise command-line user interfaces, bioseq, bioaln, biotree, and biopop, specialized for manipulation of molecular sequences, sequence alignments, phylogenetic trees, and DNA polymorphisms, respectively. Over a hundred methods are currently available as command-line options and new methods are easily incorporated. Performance of BpWrapper utilities lags that of precompiled utilities while equivalent to that of other utilities based on BioPerl. BpWrapper has been tested on BioPerl Release 1.6, Perl versions 5.10.1 to 5.25.10, and operating systems including Apple macOS, Microsoft Windows, and GNU/Linux. Release code is available from the Comprehensive Perl Archive Network (CPAN) at https://metacpan.org/pod/Bio::BPWrapper . Source code is available on GitHub at https://github.com/bioperl/p5-bpwrapper . CONCLUSIONS: BpWrapper improves on existing sequence utilities by following the design principles of Unix text utilities such including a concise user interface, extensive command-line options, and standard input/output for serialized operations. Further, dozens of novel methods for manipulation of sequences, alignments, and phylogenetic trees, unavailable in existing utilities (e.g., EMBOSS, Newick Utilities, and FAST), are provided. Bioinformaticians should find BpWrapper useful for rapid prototyping of workflows on the command-line without creating custom scripts for comparative genomics and other bioinformatics applications.

Primordial origin and diversification of plasmids in Lyme disease agent bacteria.

BACKGROUND: With approximately one-third of their genomes consisting of linear and circular plasmids, the Lyme disease agent cluster of species has the most complex genomes among known bacteria. We report here a comparative analysis of plasmids in eleven Borreliella (also known as Borrelia burgdorferi sensu lato) species. RESULTS: We sequenced the complete genomes of two B. afzelii, two B. garinii, and individual B. spielmanii, B. bissettiae, B. valaisiana and B. finlandensis isolates. These individual isolates carry between seven and sixteen plasmids, and together harbor 99 plasmids. We report here a comparative analysis of these plasmids, along with 70 additional Borreliella plasmids available in the public sequence databases. We identify only one new putative plasmid compatibility type (the 30th) among these 169 plasmid sequences, suggesting that all or nearly all such types have now been discovered. We find that the linear plasmids in the non-B. burgdorferi species have undergone the same kinds of apparently random, chaotic rearrangements mediated by non-homologous recombination that we previously discovered in B. burgdorferi. These rearrangements occurred independently in the different species lineages, and they, along with an expanded chromosomal phylogeny reported here, allow the identification of several whole plasmid transfer events among these species. Phylogenetic analyses of the plasmid partition genes show that a majority of the plasmid compatibility types arose early, most likely before separation of the Lyme agent Borreliella and relapsing fever Borrelia clades, and this, with occasional cross species plasmid transfers, has resulted in few if any species-specific or geographic region-specific Borreliella plasmid types. CONCLUSIONS: The primordial origin and persistent maintenance of the Borreliella plasmid types support their functional indispensability as well as evolutionary roles in facilitating genome diversity. The improved resolution of Borreliella plasmid phylogeny based on conserved partition-gene clusters will lead to better determination of gene orthology which is essential for prediction of biological function, and it will provide a basis for inferring detailed evolutionary mechanisms of Borreliella genomic variability including homologous gene and plasmid exchanges as well as non-homologous rearrangements.

Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network.

Bacteria of many species rely on a simple molecule, the intracellular secondary messenger c-di-GMP (Bis-(3'-5')-cyclic dimeric guanosine monophosphate), to make a vital choice: whether to stay in one place and form a biofilm, or to leave it in search of better conditions. The c-di-GMP network has a bow-tie shaped architecture that integrates many signals from the outside world-the input stimuli-into intracellular c-di-GMP levels that then regulate genes for biofilm formation or for swarming motility-the output phenotypes. How does the 'uninformed' process of evolution produce a network with the right input/output association and enable bacteria to make the right choice? Inspired by new data from 28 clinical isolates of Pseudomonas aeruginosa and strains evolved in laboratory experiments we propose a mathematical model where the c-di-GMP network is analogous to a machine learning classifier. The analogy immediately suggests a mechanism for learning through evolution: adaptation though incremental changes in c-di-GMP network proteins acquires knowledge from past experiences and enables bacteria to use it to direct future behaviors. Our model clarifies the elusive function of the ubiquitous c-di-GMP network, a key regulator of bacterial social traits associated with virulence. More broadly, the link between evolution and machine learning can help explain how natural selection across fluctuating environments produces networks that enable living organisms to make sophisticated decisions.