Human Dispersal Out of Africa: A Lasting Debate

Unraveling the first migrations of anatomically modern humans out of Africa has invoked great interest among researchers from a wide range of disciplines. Available fossil, archeological, and climatic data offer many hypotheses, and as such genetics, with the advent of genome-wide genotyping and sequencing techniques and an increase in the availability of ancient samples, offers another important tool for testing theories relating to our own history. In this review, we report the ongoing debates regarding how and when our ancestors left Africa, how many waves of dispersal there were and what geographical routes were taken. We explore the validity of each, using current genetic literature coupled with some of the key archeological findings

Metagenomic evidence for a polymicrobial signature of sepsis

Our understanding of the host component of sepsis has made significant progress. However, detailed study of the microorganisms causing sepsis, either as single pathogens or microbial assemblages, has received far less attention. Metagenomic data offer opportunities to characterize the microbial communities found in septic and healthy individuals. In this study we apply gradient-boosted tree classifiers and a novel computational decontamination technique built upon SHapley Additive exPlanations (SHAP) to identify microbial hallmarks which discriminate blood metagenomic samples of septic patients from that of healthy individuals. Classifiers had high performance when using the read assignments to microbial genera [area under the receiver operating characteristic (AUROC=0.995)], including after removal of species ‘culture-confirmed’ as the cause of sepsis through clinical testing (AUROC=0.915). Models trained on single genera were inferior to those employing a polymicrobial model and we identified multiple co-occurring bacterial genera absent from healthy controls. While prevailing diagnostic paradigms seek to identify single pathogens, our results point to the involvement of a polymicrobial community in sepsis. We demonstrate the importance of the microbial component in characterising sepsis, which may offer new biological insights into the aetiology of sepsis, and ultimately support the development of clinical diagnostic or even prognostic tools

Large-scale network analysis captures biological features of bacterial plasmids

Many bacteria can exchange genetic material through horizontal gene transfer (HGT) mediated by plasmids and plasmid-borne transposable elements. Here, we study the population structure and dynamics of over 10,000 bacterial plasmids, by quantifying their genetic similarities and reconstructing a network based on their shared k-mer content. We use a community detection algorithm to assign plasmids into cliques, which correlate with plasmid gene content, bacterial host range, GC content, and existing classifications based on replicon and mobility (MOB) types. Further analysis of plasmid population structure allows us to uncover candidates for yet undescribed replicon genes, and to identify transposable elements as the main drivers of HGT at broad phylogenetic scales. Our work illustrates the potential of network-based analyses of the bacterial ‘mobilome’ and opens up the prospect of a natural, exhaustive classification framework for bacterial plasmids

Pre-existing T cell-mediated cross-reactivity to SARS-CoV-2 cannot solely be explained by prior exposure to endemic human coronaviruses

T-cell-mediated immunity to SARS-CoV-2-derived peptides in individuals unexposed to SARS-CoV-2 has been previously reported. This pre-existing immunity was suggested to largely derive from prior exposure to ‘common cold’ endemic human coronaviruses (HCoVs). To test this, we characterised the sequence homology of SARS-CoV-2-derived T-cell epitopes reported in the literature across the full proteome of the Coronaviridae family. 54.8% of these epitopes had no homology to any of the HCoVs. Further, the proportion of SARS-CoV-2-derived epitopes with any level of sequence homology to the proteins encoded by any of the coronaviruses tested is well-predicted by their alignment-free phylogenetic distance to SARS-CoV-2 (Pearson's r = −0.958). No coronavirus in our dataset showed a significant excess of T-cell epitope homology relative to the proportion of expected random matches, given their genetic similarity to SARS-CoV-2. Our findings suggest that prior exposure to human or animal-associated coronaviruses cannot completely explain the T-cell repertoire in unexposed individuals that recognise SARS-CoV-2 cross-reactive epitopes

Molecule-by-Molecule Writing Using a Focused Electron Beam

The resolution of lithography techniques needs to be extended beyond their current limits to continue the trend of miniaturization and enable new applications. But what is the ultimate spatial resolution? It is known that single atoms can be imaged with a highly focused electron beam. Can single atoms also be written with an electron beam? We verify this with focused electron-beam-induced deposition (FEBID), a direct-write technique that has the current record for the smallest feature written by (electron) optical lithography. We show that the deposition of an organometallic precursor on graphene can be followed molecule-by-molecule with FEBID. The results show that mechanisms that are inherent to the process inhibit a further increase in control over the process. Hence, our results present the resolution limit of (electron) optical lithography techniques. The writing of isolated, subnanometer features with nanometer precision can be used, for instance, for the local modification of graphene and for catalysis.</p

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

Genomic epidemiology of the first epidemic wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Palestine.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the COVID-19 pandemic, continues to cause a significant public-health burden and disruption globally. Genomic epidemiology approaches point to most countries in the world having experienced many independent introductions of SARS-CoV-2 during the early stages of the pandemic. However, this situation may change with local lockdown policies and restrictions on travel, leading to the emergence of more geographically structured viral populations and lineages transmitting locally. Here, we report the first SARS-CoV-2 genomes from Palestine sampled from early March 2020, when the first cases were observed, through to August of 2020. SARS-CoV-2 genomes from Palestine fall across the diversity of the global phylogeny, consistent with at least nine independent introductions into the region. We identify one locally predominant lineage in circulation represented by 50 Palestinian SARS-CoV-2, grouping with genomes generated from Israel and the UK. We estimate the age of introduction of this lineage to 05/02/2020 (16/01/2020-19/02/2020), suggesting SARS-CoV-2 was already in circulation in Palestine predating its first detection in Bethlehem in early March. Our work highlights the value of ongoing genomic surveillance and monitoring to reconstruct the epidemiology of COVID-19 at both local and global scales

Genomic analysis of 18th-century kazakh individuals and their oral microbiome

The Asian Central Steppe, consisting of current-day Kazakhstan and Russia, has acted as a highway for major migrations throughout history. Therefore, describing the genetic composition of past populations in Central Asia holds value to understanding human mobility in this pivotal region. In this study, we analyse paleogenomic data generated from five humans from Kuygenzhar, Kazakhstan. These individuals date to the early to mid-18th century, shortly after the Kazakh Khanate was founded, a union of nomadic tribes of Mongol Golden Horde and Turkic origins. Genomic analysis identifies that these individuals are admixed with varying proportions of East Asian ancestry, indicating a recent admixture event from East Asia. The high amounts of DNA from the anaerobic Gram-negative bacteria Tannerella forsythia, a periodontal pathogen, recovered from their teeth suggest they may have suffered from periodontitis disease. Genomic analysis of this bacterium identified recently evolved virulence and glycosylation genes including the presence of antibiotic resistance genes predating the antibiotic era. This study provides an integrated analysis of individuals with a diet mostly based on meat (mainly horse and lamb), milk, and dairy products and their oral microbiome