We recently described Hi-Plex, a highly multiplexed PCR-based target-enrichment system for massively parallel sequencing (MPS), which allows the uniform definition of library size so that subsequent paired-end sequencing can achieve complete overlap of read pairs. Variant calling from Hi-Plex-derived datasets can thus rely on the identification of variants appearing in both reads of read-pairs, permitting stringent filtering of sequencing chemistry-induced errors. These principles underly ROVER software (derived from Read Overlap PCR-MPS variant caller), which we have recently used to report the screening for genetic mutations in the breast cancer predisposition gene PALB2. Here, we describe the algorithms underlying ROVER and its usage.

During 2018, an unusual increase in Lassa fever cases occurred in Nigeria, raising concern among national and international public health agencies. We analyzed 220 Lassa virus genomes from infected patients, including 129 from the 2017-2018 transmission season, to understand the viral populations underpinning the increase. A total of 14 initial genomes from 2018 samples were generated at Redeemer's University in Nigeria, and the findings were shared with the Nigerian Center for Disease Control in real time. We found that the increase in cases was not attributable to a particular Lassa virus strain or sustained by human-to-human transmission. Instead, the data were consistent with ongoing cross-species transmission from local rodent populations. Phylogenetic analysis also revealed extensive viral diversity that was structured according to geography, with major rivers appearing to act as barriers to migration of the rodent reservoir.

New therapeutic options to combat the growing incidence of antimicrobial resistance are urgently needed. A 2015 publication reported the isolation and biological evaluation of two diketopiperazine natural products, cyclo(l-Trp-l-Arg) (CDP 2) and cyclo(d-Trp-d-Arg) (CDP 3), from an Achromobacter sp. bacterium, finding that the latter metabolite in particular exhibited strong antibacterial activity towards a range of wound-related microorganisms and could synergize the action of ampicillin. Intrigued by these biological activities and noting inconsistencies in the structural characterization of the natural products, we synthesized the four diastereomers of cyclo(Trp-Arg) and evaluated them for antimicrobial and antibiotic enhancement properties. The detailed comparison of spectroscopic data raises uncertainty regarding the structure of CDP 2 and disproves the structure of CDP 3. In our hands, none of the four stereoisomers of cyclo(Trp-Arg) exhibited detectable intrinsic antimicrobial properties towards a range of Gram-positive and Gram-negative bacteria or fungi nor could they potentiate the action of antibiotics. These discrepancies in biological properties, compared with the activities reported in the literature, reveal that these specific cyclic dipeptides do not represent viable templates for the development of new treatments for microbial infections.

Analysis of 772 complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from early in the Boston-area epidemic revealed numerous introductions of the virus, a small number of which led to most cases. The data revealed two superspreading events. One, in a skilled nursing facility, led to rapid transmission and significant mortality in this vulnerable population but little broader spread, whereas other introductions into the facility had little effect. The second, at an international business conference, produced sustained community transmission and was exported, resulting in extensive regional, national, and international spread. The two events also differed substantially in the genetic variation they generated, suggesting varying transmission dynamics in superspreading events. Our results show how genomic epidemiology can help to understand the link between individual clusters and wider community spread.

Molecular epidemiology can provide important information regarding the genetic diversity and transmission of Plasmodium falciparum, which can assist in designing and monitoring elimination efforts. However, malaria molecular epidemiology including understanding the genetic diversity of the parasite and performing molecular surveillance of transmission has been poorly documented in Senegal. Next Generation Sequencing (NGS) offers a practical, fast and high-throughput approach to understand malaria population genetics. This study aims to unravel the population structure of P. falciparum and to estimate the allelic diversity, multiplicity of infection (MOI), and evolutionary patterns of the malaria parasite using the NGS platform.

The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.

Plasmodium vivax, one of the five species of Plasmodium parasites that cause human malaria, is responsible for 25-40% of malaria cases worldwide. Malaria global elimination efforts will benefit from accurate and effective genotyping tools that will provide insight into the population genetics and diversity of this parasite. The recent sequencing of P. vivax isolates from South America, Africa, and Asia presents a new opportunity by uncovering thousands of novel single nucleotide polymorphisms (SNPs). Genotyping a selection of these SNPs provides a robust, low-cost method of identifying parasite infections through their unique genetic signature or barcode. Based on our experience in generating a SNP barcode for P. falciparum using High Resolution Melting (HRM), we have developed a similar tool for P. vivax. We selected globally polymorphic SNPs from available P. vivax genome sequence data that were located in putatively selectively neutral sites (i.e., intergenic, intronic, or 4-fold degenerate coding). From these candidate SNPs we defined a barcode consisting of 42 SNPs. We analyzed the performance of the 42-SNP barcode on 87 P. vivax clinical samples from parasite populations in South America (Brazil, French Guiana), Africa (Ethiopia) and Asia (Sri Lanka). We found that the P. vivax barcode is robust, as it requires only a small quantity of DNA (limit of detection 0.3 ng/μl) to yield reproducible genotype calls, and detects polymorphic genotypes with high sensitivity. The markers are informative across all clinical samples evaluated (average minor allele frequency > 0.1). Population genetic and statistical analyses show the barcode captures high degrees of population diversity and differentiates geographically distinct populations. Our 42-SNP barcode provides a robust, informative, and standardized genetic marker set that accurately identifies a genomic signature for P. vivax infections.

Loss-of-function germline mutations in the PALB2 gene are associated with an increase of breast cancer risk. The purpose of this study was to characterise the spectrum of PALB2 mutations in women affected with breast or ovarian cancer from South-West Poland and West Ukraine. We applied Hi-Plex, an amplicon-based enrichment method for targeted massively parallel sequencing, to screen the coding exons and proximal intron-exon junctions of PALB2 in germline DNA from unrelated women affected with breast cancer (n = 338) and ovarian cancer (n = 89) from Poland (n = 304) and Ukraine (n = 123). These women were at high-risk of carrying a genetic predisposition to breast and/or ovarian cancer due to a family history and/or early-onset disease. Targeted-sequencing identified two frameshift deletions: PALB2:c.509_510del; p.R170Ifs in three women affected with breast cancer and PALB2:c.172_175del;p.Q60Rfs in one woman affected with ovarian cancer. A number of other previously described missense (some predicted to be damaging by PolyPhen-2 and CADD) and synonymous mutations were also identified in this population. This study is consistent with previous reports that PALB2:c.509_510del and PALB2:c.172_175del are recurrent mutations associated with breast cancer predisposition in Polish women with a family history of the disease. Our study contributes to the accumulating evidence indicating that PALB2 should be included in genetic testing for breast cancer susceptibility in these populations to enhance risk assessment and management of women at high-risk of developing breast cancer. This data could also contribute to ongoing work that is assessing the possible association between ovarian cancer risk and PALB2 mutations for which there is currently no evidence.

FANCM and RECQL have recently been reported as breast cancer susceptibility genes and it has been suggested that they should be included on gene panel tests for breast cancer predisposition. However, the clinical value of testing for mutations in RECQL and FANCM remains to be determined. In this study, we have characterised the spectrum of FANCM and RECQL mutations in women affected with breast or ovarian cancer from South-West Poland and West Ukraine.

Population-based studies of breast cancer have estimated that some PALB2 mutations confer a breast cancer risk (penetrance) comparable to the average pathogenic mutation in BRCA2. As this risk is of clinical relevance, we sought to identify mono-allelic PALB2 mutations and determine their frequencies in multiple-case breast cancer families attending Familial Cancer Clinics in Australia and New Zealand.

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortium's amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Dengue virus is a major and rapidly growing public health concern in tropic and subtropic regions across the globe. In late 2018, Senegal experienced its largest dengue virus outbreak to date, covering several regions. However, little is known about the genetic diversity of dengue virus (DENV) in Senegal. Here we report complete viral genomes from 17 previously undetected DENV cases from the city of Thiès. In total we identified 19 cases of DENV in a cohort of 198 individuals with fever collected in October and November 2018. We detected 3 co-circulating serotypes; DENV 3 was the most frequent accounting for 11/17 sequences (65%), 4 (23%) were DENV2 and 2 (12%) were DENV1. Sequences were most similar to recent sequences from West Africa, suggesting ongoing local circulation of viral populations; however, detailed inference is limited by the scarcity of available genomic data. We did not find clear associations with reported clinical signs or symptoms, highlighting the importance of testing for diagnosing febrile diseases. Overall, these findings expand the known range of DENV in Senegal, and underscore the need for better genomic characterization of DENV in West Africa.

The question of whether it is appropriate to attribute authorship to deceased individuals of original studies in the biomedical literature is contentious. Authorship guidelines utilized by journals do not provide a clear consensus framework that is binding on those in the field. To guide and inform the implementation of authorship frameworks it would be useful to understand the extent of the practice in the scientific literature, but studies that have systematically quantified the prevalence of this phenomenon in the biomedical literature have not been performed to date. To address this issue, we quantified the prevalence of publications by deceased authors in the biomedical literature from the period 1990-2020. We screened 2,601,457 peer-reviewed papers from the full text Europe PubMed Central database. We applied natural language processing, stringent filtering and manual curation to identify a final set of 1,439 deceased authors. We then determined these authors published a total of 38,907 papers over their careers with 5,477 published after death. The number of deceased publications has been growing rapidly, a 146-fold increase since the year 2000. This rate of increase was still significant when accounting for the growing total number of publications and pool of authors. We found that more than 50% of deceased author papers were first submitted after the death of the author and that over 60% of these papers failed to acknowledge the deceased authors status. Most deceased authors published less than 10 papers after death but a small pool of 30 authors published significantly more. A pool of 266 authors published more than 90% of their total publications after death. Our analysis indicates that the attribution of deceased authorship in the literature is not an occasional occurrence but a burgeoning trend. A consensus framework to address authorship by deceased scientists is warranted.

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy.

Genome sequencing can offer critical insight into pathogen spread in viral outbreaks, but existing transmission inference methods use simplistic evolutionary models and only incorporate a portion of available genetic data. Here, we develop a robust evolutionary model for transmission reconstruction that tracks the genetic composition of within-host viral populations over time and the lineages transmitted between hosts. We confirm that our model reliably describes within-host variant frequencies in a dataset of 134,682 SARS-CoV-2 deep-sequenced genomes from Massachusetts, USA. We then demonstrate that our reconstruction approach infers transmissions more accurately than two leading methods on synthetic data, as well as in a controlled outbreak of bovine respiratory syncytial virus and an epidemiologically-investigated SARS-CoV-2 outbreak in South Africa. Finally, we apply our transmission reconstruction tool to 5,692 outbreaks among the 134,682 Massachusetts genomes. Our methods and results demonstrate the utility of within-host variation for transmission inference of SARS-CoV-2 and other pathogens, and provide an adaptable mathematical framework for tracking within-host evolution.

Despite the critical role of the cardiovascular system, our understanding of its cellular and transcriptional diversity remains limited. We therefore sought to characterize the cellular composition, phenotypes, molecular pathways, and communication networks between cell types at the tissue and sub-tissue level across the cardiovascular system of the healthy Wistar rat, an important model in preclinical cardiovascular research. We obtained high quality tissue samples under controlled conditions that reveal a level of cellular detail so far inaccessible in human studies.

The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata in a cross-sectional study of febrile patients and healthy controls in a low malaria burden area. Using 16S and untargeted sequencing, we detected viral, bacterial, or eukaryotic pathogens in 23% (38/163) of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15.5% and 3.8% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium, including one putative P. ovale infection. We developed a logistic regression model that can distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs (F1 score: 0.823). These results highlight the challenge and importance of improved diagnostics, especially for Borrelia, to support diagnosis and surveillance.

Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.