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Pentalene (C8H6) and NN- and BB-bridged heterocyclic analogues (BN)4H6, derived by replacement of CC pairs with BN, are taken as  paradigms for tuning of ring-current (anti)aromaticity by variation of π charge, electronegativity and substitution pattern.  Ab initio calculation of maps for the π current density induced in these model systems by a perpendicular external magnetic field exhibits the full range of tropicity, from diatropic aromatic to nonaromatic to paratropic antiaromatic, with a ready rationalisation in terms of an orbital model.  Further calculations on systems of varying charge in which these motifs are embedded in extended PAH systems with naphthalene and phenanthrene 'clamps' show promise for switching between current patterns and related  opto-electronic properties. Particular sensitivity to charge is found for the experimentally accessible NN-bridged heteropentalene hybrids., (© 2025 Wiley‐VCH GmbH.)

The closed-shell Hückel-London-Pople-McWeeny formalism for ring currents is extended to Aufbau configurations with open shells calculated as configurational averages. The method is applied to the non-Kekulean benzenoid known as the Clar goblet, recently synthesized on the Au(111) surface. Multiplicity of the ground state is a complication: for the Clar goblet, Hund's rule of maximum multiplicity implies a triplet whereas Ovchinnikov's rule implies a singlet. This disagreement has little effect on the predicted ring currents. Ring-current maps are calculated for the 36π dication, 40π dianion, and low-lying states of the 38π neutral, using Hückel-London and Hubbard-London models. All show twin diatropic perimeter currents on separate halves of the molecule. These are compared with ipsocentric pseudo-π and ab initio maps of induced π-current for closed-shell singlet configurations of dianion, dication, and neutral. Configurationally averaged Hückel-London calculations give a good account of the consistent diatropic ring currents in the Clar goblet for the three charge states.

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 4,471,579 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of June 2024, viewable at https://viridian.taxonium.org. Each genome was constructed using a novel assembly tool called Viridian (https://github.com/iqbal-lab-org/viridian), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers., Competing Interests: Conflict of Interest Gavin Screaton sits on the GSK Vaccines Scientific Advisory Board, consults for AstraZeneca, and is a founding member of RQ Biotechnology.

Antibiotic resistance is an urgent global health challenge, necessitating rapid diagnostic tools to combat its threat. This study uses citizen science and image feature analysis to profile the cellular features associated with antibiotic resistance in Escherichia coli. Between February and April 2023, we conducted the Infection Inspection project, in which 5273 volunteers made 1,045,199 classifications of single-cell images from five E. coli strains, labelling them as antibiotic-sensitive or antibiotic-resistant based on their response to the antibiotic ciprofloxacin. User accuracy in image classification reached 66.8 ± 0.1%, lower than our deep learning model's performance at 75.3 ± 0.4%, but both users and the model were more accurate when classifying cells treated at a concentration greater than the strain's own minimum inhibitory concentration. We used the users' classifications to elucidate which visual features influence classification decisions, most importantly the degree of DNA compaction and heterogeneity. We paired our classification data with an image feature analysis which showed that most of the incorrect classifications happened when cellular features varied from the expected response. This understanding informs ongoing efforts to enhance the robustness of our diagnostic methodology. Infection Inspection is another demonstration of the potential for public participation in research, specifically increasing public awareness of antibiotic resistance., (© 2024. The Author(s).)

Optoelectronic properties of organic molecules are underpinned by delocalisation and delocalisability of π-electrons. These properties are sensitive to small changes in electron count, whether achieved by heteroatom substitution or redox chemistry. One measure of the delocalisability of π-electrons is the current induced by an external magnetic field, which is diagnostic of (anti)aromaticity. The ab initio ipsocentric method is used here to model diverse ring-current patterns in the family of [8]-circulenes based on tetracyclopenta[def,jkl,pqr,vwx]tetraphenylene (TCPTP), in different charge states, with disjoint hetero-atom substitution, and with CC units systematically replaced by BN pairs. Maps calculated at the CHF/CTOCD-DZ2/6-31G** level reveal that these modifications of the TCPTP framework access the full range of possibilities for current from concentric global circulations (typically counter rotating) to full (non-aromatic) localisation. In the ipsocentric approach, induced current density is partitioned into robust orbital contributions that obey selection rules based on orbital symmetry, energy and nodal character. The selection rules are applied here to interpret current-density and exploit insights gained from simpler models to suggest design strategies for fine-tuning of π-delocalisability (aromaticity and antiaromaticity) in macrocyclic frameworks., (© 2024 The Authors. ChemPhysChem published by Wiley-VCH GmbH.)

Background: Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis; however, antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA , encoding an enzyme that converts pyrazinamide into its active form., Methods: We curated a dataset of 664 non-redundant, missense amino acid mutations in PncA with associated high-confidence phenotypes from published studies and then trained three different machine-learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features., Results: The best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4027 samples harbouring 367 unique missense mutations in pncA derived from 24 231 clinical isolates., Conclusions: This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

Mutations in Mycobacterium tuberculosis associated with resistance to antibiotics often come with a fitness cost for the bacteria. Resistance to the first-line drug rifampicin leads to lower competitive fitness of M. tuberculosis populations when compared to susceptible populations. This fitness cost, introduced by resistance mutations in the RNA polymerase, can be alleviated by compensatory mutations (CMs) in other regions of the affected protein. CMs are of particular interest clinically since they could lock in resistance mutations, encouraging the spread of resistant strains worldwide. Here, we report the statistical inference of a comprehensive set of CMs in the RNA polymerase of M. tuberculosis , using over 70 000 M . tuberculosis genomes that were collated as part of the CRyPTIC project. The unprecedented size of this data set gave the statistical tests more power to investigate the association of putative CMs with resistance-conferring mutations. Overall, we propose 51 high-confidence CMs by means of statistical association testing and suggest hypotheses for how they exert their compensatory mechanism by mapping them onto the protein structure. In addition, we were able to show an association of CMs with higher in vitro growth densities, and hence presumably with higher fitness, in resistant samples in the more virulent M. tuberculosis lineage 2. Our results suggest the association of CM presence with significantly higher in vitro growth than for wild-type samples, although this association is confounded with lineage and sub-lineage affiliation. Our findings emphasize the integral role of CMs and lineage affiliation in resistance spread and increases the urgency of antibiotic stewardship, which implies accurate, cheap and widely accessible diagnostics for M. tuberculosis infections to not only improve patient outcomes but also prevent the spread of resistant strains.

Several bioinformatics genotyping algorithms are now commonly used to characterize antimicrobial resistance (AMR) gene profiles in whole-genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli , is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data ( n =1818 isolates) to systematically investigate genotyping methods in greater detail. Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance and SRST2, run with the ResFinder database) and their outputs compared. For simulation tests where 3079 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for 3076 (99.9 %) simulations, ABRicate for 3054 (99.2 %), ARIBA for 2783 (90.4 %) and SRST2 for 2108 (68.5 %). For simulation tests where two closely related gene variants were inserted into random sequence constructs, KmerResistance identified the correct alleles in 35 338/46 318 (76.3 %) simulations, ABRicate identified them in 11 842/46 318 (25.6 %) simulations, ARIBA identified them in 1679/46 318 (3.6 %) simulations and SRST2 identified them in 2000/46 318 (4.3 %) simulations. In real data, across all methods, 1392/1818 (76 %) isolates had discrepant allele calls for at least 1 gene. In addition to highlighting areas for improvement in challenging scenarios, (e.g. identification of AMR genes at <10× coverage, identifying multiple closely related AMR genes present in the same sample), our evaluations identified some more systematic errors that could be readily soluble, such as repeated misclassification (i.e. naming) of genes as shorter variants of the same gene present within the reference resistance gene database. Such naming errors accounted for at least 2530/4321 (59 %) of the discrepancies seen in real data. Moreover, many of the remaining discrepancies were likely 'artefactual', with reporting of cut-off differences accounting for at least 1430/4321 (33 %) discrepants. Whilst we found that comparing outputs generated by running multiple algorithms on the same dataset could identify and resolve these algorithmic artefacts, the results of our evaluations emphasize the need for developing new and more robust genotyping algorithms to further improve accuracy and performance.

Objectives: Fluoroquinolone resistance poses a threat to the successful treatment of tuberculosis. WGS, and the subsequent detection of catalogued resistance-associated mutations, offers an attractive solution to fluoroquinolone susceptibility testing but sensitivities are often less than 90%. We hypothesize that this is partly because the bioinformatic pipelines used usually mask the recognition of minor alleles that have been implicated in fluoroquinolone resistance., Methods: We analysed the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) dataset of globally diverse WGS Mycobacterium tuberculosis isolates, with matched MICs for two fluoroquinolone drugs and allowed putative minor alleles to contribute to resistance prediction., Results: Detecting minor alleles increased the sensitivity of WGS for moxifloxacin resistance prediction from 85.4% to 94.0%, without significantly reducing specificity. We also found no correlation between the proportion of an M. tuberculosis population containing a resistance-conferring allele and the magnitude of resistance., Conclusions: Together our results highlight the importance of detecting minor resistance-conferring alleles when using WGS, or indeed any sequencing-based approach, to diagnose fluoroquinolone resistance., (© The Author(s) 2023. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

Drug resistant Mycobacterium tuberculosis, which mostly results from single nucleotide polymorphisms in antibiotic target genes, poses a major threat to tuberculosis treatment outcomes. Relative binding free energy (RBFE) calculations can rapidly predict the effects of mutations, but this approach has not been tested on large, complex proteins. We use RBFE calculations to predict the effects of M. tuberculosis RNA polymerase and DNA gyrase mutations on rifampicin and moxifloxacin susceptibility respectively. These mutations encompass a range of amino acid substitutions with known effects and include large steric perturbations and charged moieties. We find that moderate numbers (n = 3-15) of short RBFE calculations can predict resistance in cases where the mutation results in a large change in the binding free energy. We show that the method lacks discrimination in cases with either a small change in energy or that involve charged amino acids, and we investigate how these calculation errors may be decreased., (© 2022 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.)

Summary: Viral sequence data from clinical samples frequently contain contaminating human reads, which must be removed prior to sharing for legal and ethical reasons. To enable host read removal for SARS-CoV-2 sequencing data on low-specification laptops, we developed ReadItAndKeep, a fast lightweight tool for Illumina and nanopore data that only keeps reads matching the SARS-CoV-2 genome. Peak RAM usage is typically below 10 MB, and runtime less than 1 min. We show that by excluding the polyA tail from the viral reference, ReadItAndKeep prevents bleed-through of human reads, whereas mapping to the human genome lets some reads escape. We believe our test approach (including all possible reads from the human genome, human samples from each of the 26 populations in the 1000 genomes data and a diverse set of SARS-CoV-2 genomes) will also be useful for others., Availability and Implementation: ReadItAndKeep is implemented in C++, released under the MIT license, and available from https://github.com/GenomePathogenAnalysisService/read-it-and-keep., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally, this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, each being present at a pre-determined concentration, thereby determining if the sample isresistant or susceptible to each sample. The minimum inhibitory concentration (MIC) of a drug is the lowestconcentration that inhibits growth and is a more useful quantity but requires each sample to be tested at a range ofconcentrations for each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is still an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing., Competing Interests: PF, CW, HS, TZ, EB, SH, AG, AR, SK, TW, TP, GM, CL, DC, DC, AW No competing interests declared, (© 2022, Fowler et al.)

Background: Molecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction., Methods: A candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation., Findings: 15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs., Interpretation: This first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes., Funding: UNITAID, Wellcome, MRC, BMGF., Competing Interests: Conflicts of interest C.U.K. is a consultant Becton Dickinson, the Foundation for Innovative New Diagnostics and the TB Alliance. C.U.K. is collaborating with Janssen, PZA Innovation and Thermo Fisher Scientific. C.U.K. worked as a consultant for QuantuMDx, the Stop TB Partnership, the World Health Organization (WHO) Global TB Programme and the WHO Regional Office for Europe. C.U.K. gave a paid educational talk for Oxford Immunotec. Hain Lifescience covered C.U.K.’s and accommodation to present at a meeting. C.U.K. is an unpaid advisor to BioVersys and GenoScreen. E.R. is employed by Public Health England and holds an honorary contract with Imperial College London. I.F.L. is Director of the Scottish Mycobacteria Reference Laboratory. S.N. receives funding from German Center for Infection Research, Excellenz Cluster Precision Medicine in Chronic Inflammation, Leibniz Science Campus Evolutionary Medicine of the LUNG (EvoLUNG)tion EXC 2167. P.S. is a consultant at Genoscreen. T.R. is funded by NIH and DoD and receives salary support from the non-profit organization FIND. T.R. is a co-founder, board member and shareholder of Verus Diagnostics Inc, a company that was founded with the intent of developing diagnostic assays. Verus Diagnostics was not involved in any way with data collection, analysis or publication of the results. T.R. has not received any financial support from Verus Diagnostics. UCSD Conflict of Interest office has reviewed and approved T.R.’s role in Verus Diagnostics Inc. T.R. is a co-inventor of a provisional patent for a TB diagnostic assay (provisional patent #: 63/048.989). T.R. is a co-inventor on a patent associated with the processing of TB sequencing data (European Patent Application No. 14840432.0 & USSN 14/912,918). T.R. has agreed to “donate all present and future interest in and rights to royalties from this patent” to UCSD to ensure that he does not receive any financial benefits from this patent. S.S. is working and holding ESOPs at HaystackAnalytics Pvt. Ltd. (Product: Using whole genome sequencing for drug susceptibility testing for Mycobacterium tuberculosis). G.F.G. is listed as an inventor on patent applications for RBD-dimer-based CoV vaccines. The patents for RBD-dimers as protein subunit vaccines for SARS-CoV-2 have been licensed to Anhui Zhifei Longcom Biopharmaceutical Co. Ltd, China. No other authors declare a conflict of interest. I.C. is a consultant for the Foundation for Innovative New Diagnostics. DAC reports funding from GlaxoSmithKline and consultancy fees from Biobeats, Oxford University Innovation, Sensyne Health.C.C. reports funding from FIND to his institution (Pathology Queensland, Queensland Department of Health) for his laboratory to perform molecular analytic studies (limits of detection) for new molecular platforms manufactured by Cepheid and Bioneer.

Tuberculosis (TB) is the leading cause of death from a single infectious agent and in 2019 an estimated 10 million people worldwide contracted the disease. Although treatments for TB exist, continual emergence of drug-resistant variants necessitates urgent development of novel antituberculars. An important new target is the lipid transporter MmpL3, which is required for construction of the unique cell envelope that shields Mycobacterium tuberculosis (Mtb) from the immune system. However, a structural understanding of the mutations in Mtb MmpL3 that confer resistance to the many preclinical leads is lacking, hampering efforts to circumvent resistance mechanisms. Here, we present the cryoelectron microscopy structure of Mtb MmpL3 and use it to comprehensively analyze the mutational landscape of drug resistance. Our data provide a rational explanation for resistance variants local to the central drug binding site, and also highlight a potential alternative route to resistance operating within the periplasmic domain., Competing Interests: Declarations of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Per iodoannulene molecules and ions C x I x q in planar geometry offer examples of systems with the potential for outer σ and inner π ring-current double aromaticity, given a sufficient overlap of tangential p σ -orbital manifolds on the large atoms of the outer cycle. Previous theoretical work indicated concentric diatropic currents in the dication C 6 I 6 2+ . Ab initio ipsocentric calculations support an account in terms of frontier-orbital selection rules for current contributions in C 6 I 6 2+ (and radical C 6 I 6 + , implicated in recent experimental work on the oxidation of per iodobenzene). A σ/π analogue of the annulene-within-an-annulene model is applied here to per iodo systems based on cyclooctatetraene. Model species C 8 I 8 q with charges q = 0, +1, +2, +4, -2 and structures constrained to a planar D 4 h symmetry exhibit maps with all combinations of σ/π con- and counter-rotation, comprising global σ ring currents on the iodine perimeter and central π ring currents on the carbocycle. All can be rationalized by the separate application of the tropicity selection rules to the two subsystems, whether in singlet or triplet states.

The emergence of antimicrobial resistance threatens modern medicine and necessitates more personalized treatment of bacterial infections. Sequencing the whole genome of the pathogen(s) in a clinical sample offers one way to improve clinical microbiology diagnostic services, and has already been adopted for tuberculosis in some countries. A key weakness of a genetics clinical microbiology is it cannot return a result for rare or novel genetic variants and therefore predictive methods are required. Non-synonymous mutations in the S. aureus dfrB gene can be successfully classified as either conferring resistance (or not) by calculating their effect on the binding free energy of the antibiotic, trimethoprim. The underlying approach, alchemical free energy methods, requires large numbers of molecular dynamics simulations to be run. We show that a large number ( N = 15) of binding free energies calculated from a series of very short (50 ps) molecular dynamics simulations are able to satisfactorily classify all seven mutations in our clinically derived testset. A result for a single mutation could therefore be returned in less than an hour, thereby demonstrating that this or similar methods are now sufficiently fast and reproducible for clinical use., Competing Interests: I declare I have no competing interest., (© 2020 The Authors.)

We model a molecular device as a molecule attached to a set of leads treated at the tight-binding level, with the central molecule described to any desired level of electronic structure theory. Within this model, in the absence of electron-phonon interactions, the Landauer-Büttiker part of the Meir-Wingreen formula is shown to be sufficient to describe the transmission factor of the correlated device. The key to this demonstration is to ensure that the correlation self-energy has the same functional form as the exact correlation self-energy. This form implies that nonsymmetric contributions to the Meir-Wingreen formula vanish, and hence, conservation of current is achieved without the need for Green's Function self-consistency. An extension of the Source-Sink-Potential (SSP) approach gives a computational route to the calculation and interpretation of electron transmission in correlated systems. In this picture, current passes through internal molecular channels via resonance states with complex-valued energies. Each resonance state arises from one of the states in the Lehmann expansion of the one-electron Green's function, hole conduction derived from ionized states, and particle conduction from attached states. In the correlated device, the dependence of transmission on electron energy is determined by four structural polynomials, as it was in the tight-binding (Hückel) version of the SSP method. Hence, there are active and inert conduction channels (in the correlated case, linked to Dyson orbitals) governed by a set of selection rules that map smoothly onto the simplest picture.

Despite a long tradition of descriptions of borazine as an 'inorganic benzene', this molecule is a non-aromatic species according to the magnetic (ring-current) criterion. Borazine, borazocine, and the larger neutral (BN)nH2n azabora-annulene heterocycles in planar conformations, although π-isoelectronic with [2n]annulenes, support only localized induced currents in perpendicular magnetic fields. The π-current maps of these systems comprise superpositions of separate 'lone-pair' circulations on all nitrogen centres. For the systems with n > 4, planarity must be enforced by a constraint. Qualitative orbital analysis based on the ipsocentric approach to calculation of induced current density suggests that global induced currents could be produced through strategic changes to the π electron count. In ab initio calculations, azabora-annulenes with rings of size [8]- and larger were indeed found to support global diatropic ring currents in both anionic and cationic forms with (4N + 2) π electron counts. The planar conformation of the charged ring typically occupies a stationary point of higher order on the potential energy surface, rather than a minimum. However, the borazocine dianion, [B4N4H8]2-, occupies a planar minimum, supports a diatropic ring current of strength comparable to that in benzene, and is predicted to participate in sandwich compounds; it is therefore a good candidate for an aromatised azabora-annulene.

As a key diagnostic property of benzenoids and other polycyclic hydrocarbons, induced ring current has inspired diverse approaches for calculation, modeling, and interpretation. Grid-based methods include the ipsocentric ab initio calculation of current maps, and its surrogate, the pseudo-π model. Graph-based models include a family of conjugated-circuit (CC) models and the molecular-orbital Hückel-London (HL) model. To assess competing claims for physical relevance of derived current maps for benzenoids, a protocol for graph-reduction and comparison was devised. Graph reduction of pseudo-π grid maps highlights their overall similarity to HL maps, but also reveals systematic differences. These are ascribed to unavoidable pseudo-π proximity limitations for benzenoids with short nonbonded distances, and to poor continuity of pseudo-π current for classes of benzenoids with fixed bonds, where single-reference methods can be unreliable. Comparison between graph-based approaches shows that the published CC models all shadow HL maps reasonably well for most benzenoids (as judged by L 1 -, L 2 -, and L ∞ -error norms on scaled bond currents), though all exhibit physically implausible currents for systems with fixed bonds. These comparisons inspire a new combinatorial model (Model W) based on cycle decomposition of current, taking into account the two terms of lowest order that occur in the characteristic polynomial. This improves on all pure-CC models within their range of applicability, giving excellent adherence to HL maps for all Kekulean benzenoids, including those with fixed bonds (halving the rms discrepancy against scaled HL bond currents, from 11% in the best CC model, to 5% for the set of 18 360 Kekulean benzenoids on up to 10 hexagonal rings). Model W also has excellent performance for open-shell systems, where currents cannot be described at all by pure CC models (4% rms discrepancy against scaled HL bond currents for the 20112 non-Kekulean benzenoids on up to 10 hexagonal rings). Consideration of largest and next-to-largest matchings is a useful strategy for modeling and interpretation of currents in Kekulean and non-Kekulean benzenoids (nanographenes).

The altanisation strategy, devised to design molecules with large and paratropic perimeter circulations, is applied to the family of [n]annulenes to give, altan-[n]annulenes, i.e. [n,5]coronenes. Analytical expressions are obtained for the eigenvalues of the Hückel Hamiltonian for altan-[n]annulenes, and used in conjunction with selection rules derived from the ipsocentric approach to predict patterns of global ring current in these systems. Density-functional calculations performed on seven altan-[n]annulenes, three neutral and four charged, give current-density maps in essential agreement with the predictions obtained at the unperturbed Hückel level. All but one of the systems show patterns with the tropicities expected for isolated annulenes, in line with the altanisation concept. The apparent exception is altan-[11]annulene-, the only singlet system with a well defined open-shell character in the studied set. The key role of open-shell character can be accommodated by appropriate choice of the occupation numbers of the initial Hückel molecular orbitals, where the anion altan-[11]annulene- is considered as an [11]annulene inside the [22]annulene anion.

Background: A comprehensive understanding of the pre-existing genetic variation in genes associated with antibiotic resistance in the Mycobacterium tuberculosis complex (MTBC) is needed to accurately interpret whole-genome sequencing data for genotypic drug susceptibility testing (DST)., Methods: We investigated mutations in 92 genes implicated in resistance to 21 anti-tuberculosis drugs using the genomes of 405 phylogenetically diverse MTBC strains. The role of phylogenetically informative mutations was assessed by routine phenotypic DST data for the first-line drugs isoniazid, rifampicin, ethambutol, and pyrazinamide from a separate collection of over 7000 clinical strains. Selected mutations/strains were further investigated by minimum inhibitory concentration (MIC) testing., Results: Out of 547 phylogenetically informative mutations identified, 138 were classified as not correlating with resistance to first-line drugs. MIC testing did not reveal a discernible impact of a Rv1979c deletion shared by M. africanum lineage 5 strains on resistance to clofazimine. Finally, we found molecular evidence that some MTBC subgroups may be hyper-susceptible to bedaquiline and clofazimine by different loss-of-function mutations affecting a drug efflux pump subunit (MmpL5)., Conclusions: Our findings underline that the genetic diversity in MTBC has to be studied more systematically to inform the design of clinical trials and to define sound epidemiologic cut-off values (ECOFFs) for new and repurposed anti-tuberculosis drugs. In that regard, our comprehensive variant catalogue provides a solid basis for the interpretation of mutations in genotypic as well as in phenotypic DST assays.

Ernzerhof's source-and-sink-potential (SSP) model for ballistic conduction in conjugated π systems predicts transmission of electrons through a two-wire device in terms of characteristic polynomials of the molecular graph and subgraphs based on the pattern of connections. We present here a complete classification of conduction properties of all molecular graphs within the SSP model. An omni-conductor/omni-insulator is a molecular graph that conducts/insulates at the Fermi level (zero of energy) for all connection patterns. In the new scheme, we define d-omni-conduction/insulation in terms of Fermi-level conduction/insulation for all devices with graph distance d between connections. This gives a natural generalisation to all graphs of the concept of near-omni-conduction/insulation previously defined for bipartite graphs only. Every molecular graph can be assigned to a nullity class and a compact code defining conduction behaviour; each graph has 0, 1, >1 zero eigenvalues (non-bonding molecular orbitals), and three letters drawn from {C, I, X} indicate conducting, insulating or mixed behaviour within the sets of devices with connection vertices at odd, even and zero distances d. Examples of graphs (in 28 cases chemical) are given for 35 of the 81 possible combinations of nullity and letter codes, and proofs of non-existence are given for 42 others, leaving only four cases open.

In Hückel theory, the bond number is the sum of the orders of the π bonds incident on a given carbon center. From the work of Coulson and his school, it has been believed for over 70 years that the bond number has a maximum of 3 and that this bound is realized by exactly one conjugated framework, that of the trimethylenemethane radical. Search of published literature and archived correspondence failed to find any formal proof of these two statements. Here, we provide a new formula for bond number that leads to an easily checked proof of both. The bond number of graphene is 1.574 597… (90.9% of the mathematical limit), and this value appears to act as a separator for the classes of metallic and semiconducting single-walled nanotubes, as defined within Hückel theory.

M. tuberculosis grows slowly and is challenging to work with experimentally compared with many other bacteria. Although microtitre plates have the potential to enable high-throughput phenotypic testing of M. tuberculosis, they can be difficult to read and interpret. Here we present a software package, the Automated Mycobacterial Growth Detection Algorithm (AMyGDA), that measures how much M. tuberculosis is growing in each well of a 96-well microtitre plate. The plate used here has serial dilutions of 14 anti-tuberculosis drugs, thereby permitting the MICs to be elucidated. The three participating laboratories each inoculated 38 96-well plates with 15 known M. tuberculosis strains (including the standard H37Rv reference strain) and, after 2 weeks' incubation, measured the MICs for all 14 drugs on each plate and took a photograph. By analysing the images, we demonstrate that AMyGDA is reproducible, and that the MICs measured are comparable to those measured by a laboratory scientist. The AMyGDA software will be used by the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) to measure the drug susceptibility profile of a large number (>30000) of samples of M. tuberculosis from patients over the next few years.

The UKMYC5 plate is a 96-well microtiter plate designed by the CRyPTIC Consortium (Comprehensive Resistance Prediction for Tuberculosis: an International Consortium) to enable the measurement of MICs of 14 different antituberculosis (anti-TB) compounds for >30,000 clinical Mycobacterium tuberculosis isolates. Unlike the MYCOTB plate, on which the UKMYC5 plate is based, the UKMYC5 plate includes two new (bedaquiline and delamanid) and two repurposed (clofazimine and linezolid) compounds. UKMYC5 plates were tested by seven laboratories on four continents by use of a panel of 19 external quality assessment (EQA) strains, including H37Rv. To assess the optimal combination of reading method and incubation time, MICs were measured from each plate by two readers, using three methods (mirrored box, microscope, and Vizion digital viewing system), after 7, 10, 14, and 21 days of incubation. In addition, all EQA strains were subjected to whole-genome sequencing and phenotypically characterized by the 7H10/7H11 agar proportion method (APM) and by use of MGIT960 mycobacterial growth indicator tubes. We concluded that the UKMYC5 plate is optimally read using the Vizion system after 14 days of incubation, achieving an interreader agreement of 97.9% and intra- and interlaboratory reproducibility rates of 95.6% and 93.1%, respectively. The mirrored box had a similar reproducibility. Strains classified as resistant by APM, MGIT960, or the presence of mutations known to confer resistance consistently showed elevated MICs compared to those for strains classified as susceptible. Finally, the UKMYC5 plate records intermediate MICs for one strain for which the APM measured MICs close to the applied critical concentration, providing early evidence that the UKMYC5 plate can quantitatively measure the magnitude of resistance to anti-TB compounds that is due to specific genetic variation., (Copyright © 2018 Rancoita et al.)

It is well known that polymerization-induced self-assembly (PISA) offers an efficient synthetic route for the production of highly anisotropic diblock copolymer worms. When prepared in aqueous media, such worms form thermoresponsive free-standing hydrogels that are (i) readily sterilizable, (ii) can act as a 3D matrix for the culture of normal mammalian cells and (iii) can induce stasis in human stem cell colonies. Herein we critically examine the gelation behavior of two types of diblock copolymer worms in terms of recent advances in percolation theory for rigid rods, which explicitly account for the effect of rod length polydispersity. More specifically, we use small-angle X-ray scattering (SAXS) to determine the weight-average worm contour length, L w , and the mean worm cross-sectional radius, R . This approach enables a direct comparison to be made between the theoretical critical worm volume fraction, φ c , required for gelation and the experimental values indicated by rheological measurements and tube inversion experiments. Given that these diblock copolymer worms are relatively flexible rather than truly rod-like, reasonably good agreement between these two parameters is observed, particularly for shorter, relatively stiff worms. For longer, more flexible worms a proportionality constant of approximately two is required to reconcile theory with experimental values for φ c . These findings are expected to have important implications for the aqueous gelation behavior exhibited by various other anisotropic nanoparticles, such as cellulose nanocrystals and semicrystalline block copolymer rods, and also fibril-forming small molecule ( e.g. dipeptide) gelators.

The rise of antibiotic resistance threatens modern medicine; to combat it new diagnostic methods are required. Sequencing the whole genome of a pathogen offers the potential to accurately determine which antibiotics will be effective to treat a patient. A key limitation of this approach is that it cannot classify rare or previously unseen mutations. Here we demonstrate that alchemical free energy methods, a well-established class of methods from computational chemistry, can successfully predict whether mutations in Staphylococcus aureus dihydrofolate reductase confer resistance to trimethoprim. We also show that the method is quantitatively accurate by calculating how much the most common resistance-conferring mutation, F99Y, reduces the binding free energy of trimethoprim and comparing predicted and experimentally measured minimum inhibitory concentrations for seven different mutations. Finally, by considering up to 32 free energy calculations for each mutation, we estimate its specificity and sensitivity., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

We illustrate that single-cell Raman microspectroscopy, coupled with deuterium isotope probing (Raman-DIP), provides a culture-independent and nondestructive approach to probe metabolic pathways of carbon substrates at the single-cell level. We found a distinguishable C-D vibration band at 2070-2300 cm -1 in single-cell Raman spectra (SCRS) when Escherichia coli used deuterated glucose and Pseudomonas sp. used deuterated naphthalene as sole carbon sources. The intensity of the C-D band is proportional to the extent of deuteration in the carbon source, and as little as 5% deuteration can be distinguished by analysis of SCRS. It suggests that Raman-DIP could be used to semiquantitatively and sensitively indicate the metabolism of deuterated carbon source in microbes. A lower lipid conversion rate of deuterated naphthalene compared to that of deuterated glucose was observed, presumably owing to different anabolic pathways and membrane alteration. Apart from the C-D band shift from C-H, SCRS also reveal several isotopic shifts of the phenylalanine band, of which the positions correlate well with a computational model. A reduction in phenylalanine deuteration in Pseudomonas sp. compared to that in E. coli is due to the dilution effect of different pathways of phenylalanine biosynthesis in Pseudomonas sp. Collectively, we demonstrate that Raman-DIP can not only indicate metabolic activity using deuterated carbon sources but also reveal different metabolic pathways by analyzing SCRS. By harnessing such low-cost and versatile deuterated substrates, Raman-DIP has the potential to probe a wide range of metabolic pathways and functions at the single-cell level.

Cell membranes are crowded and complex environments. To investigate the effect of protein-lipid interactions on dynamic organization in mammalian cell membranes, we have performed coarse-grained molecular dynamics simulations containing >100 copies of an inwardly rectifying potassium (Kir) channel which forms specific interactions with the regulatory lipid phosphatidylinositol 4,5-bisphosphate (PIP 2 ). The tendency of protein molecules to cluster has the effect of organizing the membrane into dynamic compartments. At the same time, the diversity of lipids present has a marked effect on the clustering behavior of ion channels. Sub-diffusion of proteins and lipids is observed. Protein crowding alters the sub-diffusive behavior of proteins and lipids such as PIP 2 which interact tightly with Kir channels. Protein crowding also affects bilayer properties, such as membrane undulations and bending rigidity, in a PIP 2 -dependent manner. This interplay between the diffusion and the dynamic organization of Kir channels may have important implications for channel function.

Sterically stabilized diblock copolymer nanoparticles with an intensity-average diameter of 25 nm are prepared in the form of a concentrated aqueous dispersion using polymerization-induced self-assembly (PISA). The addition of n-dodecane followed by high-shear homogenization produces n-dodecane-in-water Pickering macroemulsions of 22-46 μm diameter. If the nanoparticles are present in sufficient excess, then subsequent processing using a high-pressure microfluidizer leads to the formation of Pickering nanoemulsions with a mean oil droplet diameter below 200 nm. The size of these Pickering nanoemulsions can be tuned by systematically varying the nanoparticle concentration, applied pressure, number of passes, and oil volume fraction. High-internal-phase emulsions can also be achieved by increasing the n-dodecane volume fraction up to 0.80. TEM studies of (dried) n-dodecane droplets confirm the presence of intact nanoparticles and suggest a relatively high surface coverage, which is consistent with model packing calculations based on radius ratios. Such Pickering nanoemulsions proved to be surprisingly stable with respect to Ostwald ripening, with no significant change in the mean DLS droplet diameter after storage for approximately 4 months at 20 °C.