MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design.

The growing capabilities of synthetic biology and organic chemistry demand tools to guide syntheses toward useful molecules. Here, we present Molecular AutoenCoding Auto-Workaround (MACAW), a tool that uses a novel approach to generate molecules predicted to meet a desired property specification (e.g., a binding affinity of 50 nM or an octane number of 90). MACAW describes molecules by embedding them into a smooth multidimensional numerical space, avoiding uninformative dimensions that previous methods often introduce. The coordinates in this embedding provide a natural choice of features for accurately predicting molecular properties, which we demonstrate with examples for cetane and octane numbers, flash points, and histamine H1 receptor binding affinity. The approach is computationally efficient and well-suited to the small- and medium-size datasets commonly used in biosciences. We showcase the utility of MACAW for virtual screening by identifying molecules with high predicted binding affinity to the histamine H1 receptor and limited affinity to the muscarinic M2 receptor, which are targets of medicinal relevance. Combining these predictive capabilities with a novel generative algorithm for molecules allows us to recommend molecules with a desired property value (i.e., inverse molecular design). We demonstrate this capability by recommending molecules with predicted octane numbers of 40, 80, and 120, which is an important characteristic of biofuels. Thus, MACAW augments classical retrosynthesis tools by providing recommendations for molecules on specification.

Genomic and Synthetic Biology Digital Biosecurity.

Trends toward automation of synthetic biology and the individualization of biology and medicine raise varied and critical security issues. Digital biosecurity brings together researchers working in secure algorithms, vulnerability assessments, and emerging threat models. The fundamental goal of this digital biosecurity workshop is to identify and present distinct areas of research around making the next generation of biology safer and more secure. The workshop will include a panel overview of the field, including representatives from academia, industry, and non-profits. It will also include novel presentations from the research community. We expect that attendees will leave this workshop with a new appreciation of the research and implementation challenges in maintaining the digital aspects of biosecurity.

Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track.

BACKGROUND: Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. BASIC PROCEDURES: We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. MAIN FINDINGS: We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions. PRINCIPAL CONCLUSIONS: We show the benchmarking results of novel blockchain-based methods for institutions to share patient outcomes related to gene-drug interactions. Our findings support blockchain utilization in healthcare, genomic and biomedical applications. The source code is publicly available at https://github.com/tsungtingkuo/genedrug.

Decentralized genomics audit logging via permissioned blockchain ledgering.

BACKGROUND: One of the tasks in the iDASH Secure Genome Analysis Competition in 2018 was to develop blockchain-based immutable logging and querying for a cross-site genomic dataset access audit trail. The specific challenge was to design a time/space efficient structure and mechanism of storing/retrieving genomic data access logs, based on MultiChain version 1.0.4 ( https://www.multichain.com/ ). METHODS: Our technique uses the MultiChain stream application programming interface (which affords treating MultiChain as a key value store) and employs a two-level index, which naturally supports efficient queries of the data for single clause constraints. The scheme also supports heuristic and binary search techniques for queries containing conjunctions of clause constraints, and timestamp range queries. Of note, all of our techniques have complexity independent of inserted data set size, other than the timestamp ranges, which logarithmically scale with input size. RESULTS: We implemented our insertion and querying techniques in Python, using the MultiChain library Savoir ( https://github.com/dxmarkets/savoir ), and comprehensively tested our implementation across a benchmark of datasets of varying sizes. We also tested a port of our challenge submission to a newer version of MultiChain (2.0 beta), which natively supports multiple indices. CONCLUSIONS: We presented creative and efficient techniques for storing and querying log file data in MultiChain 1.0.4 and 2.0 beta. We demonstrated that it is feasible to use a permissioned blockchain ledger for genomic query log data when data volume is on the order of hundreds of megabytes and query times of dozens of minutes is acceptable. We demonstrated that evolution in the ledger platform (MultiChain 1 to 2) yielded a 30%-40% increase in insertion efficiency. All source code for this challenge has been made available under a BSD-3 license from https://github.com/sandialabs/idash2018task1/ .

New candidates for regulated gene integrity revealed through precise mapping of integrative genetic elements.

Integrative genetic elements (IGEs) are mobile multigene DNA units that integrate into and excise from host bacterial genomes. Each IGE usually targets a specific site within a conserved host gene, integrating in a manner that preserves target gene function. However, a small number of bacterial genes are known to be inactivated upon IGE integration and reactivated upon excision, regulating phenotypes of virulence, mutation rate, and terminal differentiation in multicellular bacteria. The list of regulated gene integrity (RGI) cases has been slow-growing because IGEs have been challenging to precisely and comprehensively locate in genomes. We present software (TIGER) that maps IGEs with unprecedented precision and without attB site bias. TIGER uses a comparative genomic, ping-pong BLAST approach, based on the principle that the IGE integration module (i.e. its int-attP region) is cohesive. The resultant IGEs from 2168 genomes, along with integrase phylogenetic analysis and gene inactivation tests, revealed 19 new cases of genes whose integrity is regulated by IGEs (including dut, eccCa1, gntT, hrpB, merA, ompN, prkA, tqsA, traG, yifB, yfaT and ynfE), as well as recovering previously known cases (in sigK, spsM, comK, mlrA and hlb genes). It also recovered known clades of site-promiscuous integrases and identified possible new ones.

CasCollect: targeted assembly of CRISPR-associated operons from high-throughput sequencing data.

CRISPR arrays and CRISPR-associated (Cas) proteins comprise a widespread adaptive immune system in bacteria and archaea. These systems function as a defense against exogenous parasitic mobile genetic elements that include bacteriophages, plasmids and foreign nucleic acids. With the continuous spread of antibiotic resistance, knowledge of pathogen susceptibility to bacteriophage therapy is becoming more critical. Additionally, gene-editing applications would benefit from the discovery of new cas genes with favorable properties. While next-generation sequencing has produced staggering quantities of data, transitioning from raw sequencing reads to the identification of CRISPR/Cas systems has remained challenging. This is especially true for metagenomic data, which has the highest potential for identifying novel cas genes. We report a comprehensive computational pipeline, CasCollect, for the targeted assembly and annotation of cas genes and CRISPR arrays-even isolated arrays-from raw sequencing reads. Benchmarking our targeted assembly pipeline demonstrates significantly improved timing by almost two orders of magnitude compared with conventional assembly and annotation, while retaining the ability to detect CRISPR arrays and cas genes. CasCollect is a highly versatile pipeline and can be used for targeted assembly of any specialty gene set, reconfigurable for user provided Hidden Markov Models and/or reference nucleotide sequences.

RetSynth: determining all optimal and sub-optimal synthetic pathways that facilitate synthesis of target compounds in chassis organisms.

BACKGROUND: The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical in a chassis organism is computationally intractable. Many current methods provide a single solution to this problem, but fail to provide all optimal pathways, optional sub-optimal solutions or hybrid biological/non-biological solutions. RESULTS: Here we present RetSynth, software with a novel algorithm for determining all optimal biological pathways given a starting biological chassis and target chemical. By dynamically selecting constraints, the number of potential pathways scales by the number of fully independent pathways and not by the number of overall reactions or size of the metabolic network. This feature allows all optimal pathways to be determined for a large number of chemicals and for a large corpus of potential chassis organisms. Additionally, this software contains other features including the ability to collect data from metabolic repositories, perform flux balance analysis, and to view optimal pathways identified by our algorithm using a built-in visualization module. This software also identifies sub-optimal pathways and allows incorporation of non-biological chemical reactions, which may be performed after metabolic production of precursor molecules. CONCLUSIONS: The novel algorithm designed for RetSynth streamlines an arduous and complex process in metabolic engineering. Our stand-alone software allows the identification of candidate optimal and additional sub-optimal pathways, and provides the user with necessary ranking criteria such as target yield to decide which route to select for target production. Furthermore, the ability to incorporate non-biological reactions into the final steps allows determination of pathways to production for targets that cannot be solely produced biologically. With this comprehensive suite of features RetSynth exceeds any open-source software or webservice currently available for identifying optimal pathways for target production.

Defending Our Public Biological Databases as a Global Critical Infrastructure.

Progress in modern biology is being driven, in part, by the large amounts of freely available data in public resources such as the International Nucleotide Sequence Database Collaboration (INSDC), the world's primary database of biological sequence (and related) information. INSDC and similar databases have dramatically increased the pace of fundamental biological discovery and enabled a host of innovative therapeutic, diagnostic, and forensic applications. However, as high-value, openly shared resources with a high degree of assumed trust, these repositories share compelling similarities to the early days of the Internet. Consequently, as public biological databases continue to increase in size and importance, we expect that they will face the same threats as undefended cyberspace. There is a unique opportunity, before a significant breach and loss of trust occurs, to ensure they evolve with quality and security as a design philosophy rather than costly "retrofitted" mitigations. This Perspective surveys some potential quality assurance and security weaknesses in existing open genomic and proteomic repositories, describes methods to mitigate the likelihood of both intentional and unintentional errors, and offers recommendations for risk mitigation based on lessons learned from cybersecurity.

Experimental single-strain mobilomics reveals events that shape pathogen emergence.

Virulence genes on mobile DNAs such as genomic islands (GIs) and plasmids promote bacterial pathogen emergence. Excision is an early step in GI mobilization, producing a circular GI and a deletion site in the chromosome; circular forms are also known for some bacterial insertion sequences (ISs). The recombinant sequence at the junctions of such circles and deletions can be detected sensitively in high-throughput sequencing data, using new computational methods that enable empirical discovery of mobile DNAs. For the rich mobilome of a hospital Klebsiella pneumoniae strain, circularization junctions (CJs) were detected for six GIs and seven IS types. Our methods revealed differential biology of multiple mobile DNAs, imprecision of integrases and transposases, and differential activity among identical IS copies for IS26, ISKpn18 and ISKpn21 Using the resistance of circular dsDNA molecules to exonuclease, internally calibrated with the native plasmids, showed that not all molecules bearing GI CJs were circular. Transpositions were also detected, revealing replicon preference (ISKpn18 prefers a conjugative IncA/C2 plasmid), local action (IS26), regional preferences, selection (against capsule synthesis) and IS polarity inversion. Efficient discovery and global characterization of numerous mobile elements per experiment improves accounting for the new gene combinations that arise in emerging pathogens.

Lignin-modifying processes in the rhizosphere of arid land grasses.

Genes associated with elevated oxidative enzyme activities in arid systems have not been well characterized. To link measured oxidative activities with specific enzymes, we assembled protein-coding reads from the rhizospheres (RHZ) of two arid land grasses. Targeted gene scans for open reading frames, encoding genes potentially involved in lignin modification, resulted in 127 distinct assembly products. The putative genes included those significantly similar to Class II secretory fungal peroxidases. These genes are expressed at sufficiently high levels for assembly, annotation and differentiation across experimental conditions, and they demonstrate the interplay of root systems, environment and plant microbiomes. The genes assembled also included copper-dependent lytic polysaccharide monooxygenases. We detail the enzymes in the host grass RHZs and present a preliminary taxonomic microhabitat characterization. Our findings provide support for biologically mediated Fenton chemistry in the root zones of desert grasses, and provide insight into arid land carbon flow. These results also demonstrate a hyperdiverse microbial community. Both ribosomal RNA and messenger RNA sequences were dominated by bacteria, followed by fungal sequence abundance. Among the notable fungal sequences were those from the members of the arbuscular mycorrhizal fungi (Glomeromycota), which though abundant in this study, we rarely observed in previous PCR-based surveys.

Islander: a database of precisely mapped genomic islands in tRNA and tmRNA genes.

Genomic islands are mobile DNAs that are major agents of bacterial and archaeal evolution. Integration into prokaryotic chromosomes usually occurs site-specifically at tRNA or tmRNA gene (together, tDNA) targets, catalyzed by tyrosine integrases. This splits the target gene, yet sequences within the island restore the disrupted gene; the regenerated target and its displaced fragment precisely mark the endpoints of the island. We applied this principle to search for islands in genomic DNA sequences. Our algorithm identifies tDNAs, finds fragments of those tDNAs in the same replicon and removes unlikely candidate islands through a series of filters. A search for islands in 2168 whole prokaryotic genomes produced 3919 candidates. The website Islander (recently moved to http://bioinformatics.sandia.gov/islander/) presents these precisely mapped candidate islands, the gene content and the island sequence. The algorithm further insists that each island encode an integrase, and attachment site sequence identity is carefully noted; therefore, the database also serves in the study of integrase site-specificity and its evolution.

The tmRNA website.

The transfer-messenger RNA (tmRNA) and its partner protein SmpB act together in resolving problems arising when translating bacterial ribosomes reach the end of mRNA with no stop codon. Their genes have been found in nearly all bacterial genomes and in some organelles. The tmRNA Website serves tmRNA sequences, alignments and feature annotations, and has recently moved to http://bioinformatics.sandia.gov/tmrna/. New features include software used to find the sequences, an update raising the number of unique tmRNA sequences from 492 to 1716, and a database of SmpB sequences which are served along with the tmRNA sequence from the same organism.

RNAcentral: an international database of ncRNA sequences.

The field of non-coding RNA biology has been hampered by the lack of availability of a comprehensive, up-to-date collection of accessioned RNA sequences. Here we present the first release of RNAcentral, a database that collates and integrates information from an international consortium of established RNA sequence databases. The initial release contains over 8.1 million sequences, including representatives of all major functional classes. A web portal (http://rnacentral.org) provides free access to data, search functionality, cross-references, source code and an integrated genome browser for selected species.

Ends of the line for tmRNA-SmpB.

Genes for the RNA tmRNA and protein SmpB, partners in the trans-translation process that rescues stalled ribosomes, have previously been found in all bacteria and some organelles. During a major update of The tmRNA Website (relocated to http://bioinformatics.sandia.gov/tmrna), including addition of an SmpB sequence database, we found some bacteria that lack functionally significant regions of SmpB. Three groups with reduced genomes have lost the central loop of SmpB, which is thought to improve alanylation and EF-Tu activation: Carsonella, Hodgkinia, and the hemoplasmas (hemotropic Mycoplasma). Carsonella has also lost the SmpB C-terminal tail, thought to stimulate the decoding center of the ribosome. We validate recent identification of tmRNA homologs in oomycete mitochondria by finding partner genes from oomycete nuclei that target SmpB to the mitochondrion. We have moreover identified through exhaustive search a small number of complete, but often highly derived, bacterial genomes that appear to lack a functional copy of either the tmRNA or SmpB gene (but not both). One Carsonella isolate exhibits complete degradation of the tmRNA gene sequence yet its smpB shows no evidence for relaxed selective constraint, relative to other genes in the genome. After loss of the SmpB central loop in the hemoplasmas, one subclade apparently lost tmRNA. Carsonella also exhibits gene overlap such that tmRNA maturation should produce a non-stop smpB mRNA. At least some of the tmRNA/SmpB-deficient strains appear to further lack the ArfA and ArfB backup systems for ribosome rescue. The most frequent neighbors of smpB are the tmRNA gene, a ratA/rnfH unit, and the gene for RNaseR, a known physical and functional partner of tmRNA-SmpB.

Definitive assignment by multigenome analysis of the gammaproteobacterial genus Thermithiobacillus to the class Acidithiobacillia.

The class Acidithiobacillia was established using multiprotein phylogenetic analysis of all the available genomes of the genus Acidithiobacillus (comprising Family I, the Acidithiobacillaceae, of the Acidithiobacillales, the order created for Bergey's Manual of Systematic Bacteriology), and for representative genomes of all available bacterial orders. The Acidithiobacillales contain a second family, the Thermithiobacillaceae, represented by Thermithiobacillus tepidarius, and created on the basis of nearest neighbour 16S ribosomal RNA gene sequence similarities. This could not be included in the original multiprotein analysis as no genome sequence for Thermithio bacillus was available. The publication of the genome sequence of Thermithiobacillus tepidarius in 2013 has enabled phylogenetic assessment of this organism by comparative multigenome analysis. This shows definitively that Thermithiobacillus is a member of the class Acidithiobacillia, distinct from the Acidithiobacillus genus, and confirms it to represent a second family within the Acidithiobacillia.

Resistance determinants and mobile genetic elements of an NDM-1-encoding Klebsiella pneumoniae strain.

Multidrug-resistant Enterobacteriaceae are emerging as a serious infectious disease challenge. These strains can accumulate many antibiotic resistance genes though horizontal transfer of genetic elements, those for ß-lactamases being of particular concern. Some ß-lactamases are active on a broad spectrum of ß-lactams including the last-resort carbapenems. The gene for the broad-spectrum and carbapenem-active metallo-ß-lactamase NDM-1 is rapidly spreading. We present the complete genome of Klebsiella pneumoniae ATCC BAA-2146, the first U.S. isolate found to encode NDM-1, and describe its repertoire of antibiotic-resistance genes and mutations, including genes for eight ß-lactamases and 15 additional antibiotic-resistance enzymes. To elucidate the evolution of this rich repertoire, the mobile elements of the genome were characterized, including four plasmids with varying degrees of conservation and mosaicism and eleven chromosomal genomic islands. One island was identified by a novel phylogenomic approach, that further indicated the cps-lps polysaccharide synthesis locus, where operon translocation and fusion was noted. Unique plasmid segments and mosaic junctions were identified. Plasmid-borne blaCTX-M-15 was transposed recently to the chromosome by ISEcp1. None of the eleven full copies of IS26, the most frequent IS element in the genome, had the expected 8-bp direct repeat of the integration target sequence, suggesting that each copy underwent homologous recombination subsequent to its last transposition event. Comparative analysis likewise indicates IS26 as a frequent recombinational junction between plasmid ancestors, and also indicates a resolvase site. In one novel use of high-throughput sequencing, homologously recombinant subpopulations of the bacterial culture were detected. In a second novel use, circular transposition intermediates were detected for the novel insertion sequence ISKpn21 of the ISNCY family, suggesting that it uses the two-step transposition mechanism of IS3. Robust genome-based phylogeny showed that a unified Klebsiella cluster contains Enterobacter aerogenes and Raoultella, suggesting the latter genus should be abandoned.

A conserved mammalian protein interaction network.

Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

Metabolic and evolutionary costs of herbivory defense: systems biology of glucosinolate synthesis.

Here, we describe our updated mathematical model of Arabidopsis thaliana Columbia metabolism, which adds the glucosinolates, an important group of secondary metabolites, to the reactions of primary metabolism. In so doing, we also describe the evolutionary origins of the enzymes involved in glucosinolate synthesis. We use this model to address a long-standing question in plant evolutionary biology: whether or not apparently defensive compounds such as glucosinolates are metabolically costly to produce. We use flux balance analysis to estimate the flux through every metabolic reaction in the model both when glucosinolates are synthesized and when they are absent. As a result, we can compare the metabolic costs of cell synthesis with and without these compounds, as well as inferring which reactions have their flux altered by glucosinolate synthesis. We find that glucosinolate production can increase photosynthetic requirements by at least 15% and that this cost is specific to the suite of glucosinolates found in A. thaliana, with other combinations of glucosinolates being even more costly. These observations suggest that glucosinolates have evolved, and indeed likely continue to evolve, for herbivory defense, since only this interpretation explains the maintenance of such costly traits.

Selection for higher gene copy number after different types of plant gene duplications.

The evolutionary origins of the multitude of duplicate genes in the plant genomes are still incompletely understood. To gain an appreciation of the potential selective forces acting on these duplicates, we phylogenetically inferred the set of metabolic gene families from 10 flowering plant (angiosperm) genomes. We then compared the metabolic fluxes for these families, predicted using the Arabidopsis thaliana and Sorghum bicolor metabolic networks, with the families' duplication propensities. For duplications produced by both small scale (small-scale duplications) and genome duplication (whole-genome duplications), there is a significant association between the flux and the tendency to duplicate. Following this global analysis, we made a more fine-scale study of the selective constraints observed on plant sodium and phosphate transporters. We find that the different duplication mechanisms give rise to differing selective constraints. However, the exact nature of this pattern varies between the gene families, and we argue that the duplication mechanism alone does not define a duplicated gene's subsequent evolutionary trajectory. Collectively, our results argue for the interplay of history, function, and selection in shaping the duplicate gene evolution in plants.

Expression level, cellular compartment and metabolic network position all influence the average selective constraint on mammalian enzymes.

BACKGROUND: A gene's position in regulatory, protein interaction or metabolic networks can be predictive of the strength of purifying selection acting on it, but these relationships are neither universal nor invariably strong. Following work in bacteria, fungi and invertebrate animals, we explore the relationship between selective constraint and metabolic function in mammals. RESULTS: We measure the association between selective constraint, estimated by the ratio of nonsynonymous (Ka) to synonymous (Ks) substitutions, and several, primarily metabolic, measures of gene function. We find significant differences between the selective constraints acting on enzyme-coding genes from different cellular compartments, with the nucleus showing higher constraint than genes from either the cytoplasm or the mitochondria. Among metabolic genes, the centrality of an enzyme in the metabolic network is significantly correlated with Ka/Ks. In contrast to yeasts, gene expression magnitude does not appear to be the primary predictor of selective constraint in these organisms. CONCLUSIONS: Our results imply that the relationship between selective constraint and enzyme centrality is complex: the strength of selective constraint acting on mammalian genes is quite variable and does not appear to exclusively follow patterns seen in other organisms.