Streptococcus pneumoniae is a significant human pathogen and a leading cause of infant mortality in developing countries. Considerable global variation in the pneumococcal carriage prevalence has been observed and the ecological factors contributing to it are not yet fully understood. We use data from a cohort of infants in Asia to study the effects of climatic conditions on both acquisition and clearance rates of the bacterium, finding significantly higher transmissibility during the cooler and drier months. Conversely, the length of a colonization period is unaffected by the season. Independent carriage data from studies conducted on the African and North American continents suggest similar effects of the climate on the prevalence of this bacterium, which further validates the obtained results. Further studies could be important to replicate the findings and explain the mechanistic role of cooler and dry air in the physiological response to nasopharyngeal acquisition of the pneumococcus.

Prokaryotic evolution is affected by horizontal transfer of genetic material through recombination. Inference of an evolutionary tree of bacteria thus relies on accurate identification of the population genetic structure and recombination-derived mosaicism. Rapidly growing databases represent a challenge for computational methods to detect recombinations in bacterial genomes. We introduce a novel algorithm called fastGEAR which identifies lineages in diverse microbial alignments, and recombinations between them and from external origins. The algorithm detects both recent recombinations (affecting a few isolates) and ancestral recombinations between detected lineages (affecting entire lineages), thus providing insight into recombinations affecting deep branches of the phylogenetic tree. In simulations, fastGEAR had comparable power to detect recent recombinations and outstanding power to detect the ancestral ones, compared with state-of-the-art methods, often with a fraction of computational cost. We demonstrate the utility of the method by analyzing a collection of 616 whole-genomes of a recombinogenic pathogen Streptococcus pneumoniae, for which the method provided a high-resolution view of recombination across the genome. We examined in detail the penicillin-binding genes across the Streptococcus genus, demonstrating previously undetected genetic exchanges between different species at these three loci. Hence, fastGEAR can be readily applied to investigate mosaicism in bacterial genes across multiple species. Finally, fastGEAR correctly identified many known recombination hotspots and pointed to potential new ones. Matlab code and Linux/Windows executables are available at https://users.ics.aalto.fi/similar to pemartti/fastGEAR/ (last accessed February 6, 2017).

Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein- protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.

Streptococcus pneumoniae can be divided into many strains, each a distinct set of isolates sharing similar core and accessory genomes, which co-circulate within the same hosts. Previous analyses suggested the short-term vaccine-associated dynamics of S. pneumoniae strains may be mediated through multi-locus negative frequency-dependent selection (NFDS), which maintains accessory loci at equilibrium frequencies. Long-term simulations demonstrated NFDS stabilised clonally-evolving multi-strain populations through preventing the loss of variation through drift, based on polymorphism frequencies, pairwise genetic distances and phylogenies. However, allowing symmetrical recombination between isolates evolving under multi-locus NFDS generated unstructured populations of diverse genotypes. Replication of the observed data improved when multi-locus NFDS was combined with recombination that was instead asymmetrical, favouring deletion of accessory loci over insertion. This combination separated populations into strains through outbreeding depression, resulting from recombinants with reduced accessory genomes having lower fitness than their parental genotypes. Although simplistic modelling of recombination likely limited these simulations' ability to maintain some properties of genomic data as accurately as those lacking recombination, the combination of asymmetrical recombination and multi-locus NFDS could restore multi-strain population structures from randomised initial populations. As many bacteria inhibit insertions into their chromosomes, this combination may commonly underlie the co-existence of strains within a niche.

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce PANINI (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. PANINI is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. PANINI is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini.

Children in Angola are affected by a high burden of disease caused by pneumococcal infections. The 13-valent pneumococcal conjugate vaccine (PCV13) was introduced in the childhood immunization programme in 2013 but the serotype distribution of Streptococcus pneumoniae and antimicrobial susceptibility patterns are unknown. We did a cross-sectional nasopharyngeal carriage study in Luanda and Saurimo, Angola (PCV13 3rd dose coverage 67% and 84%, respectively) during November to December 2017 comprising 940 children aged 4-12 years. The main objective was to assess vaccine serotype coverage and antimicrobial susceptibility rates for S. pneumoniae. Our secondary aim was to characterize colonizinig strains of Haemophilus influenzae and Moraxella catarrhalis. Pneumococcal colonization was found in 35% (95% CI 32-39%) of children (n = 332), with 41% of serotypes covered by PCV13. The most common serotypes were 3 (8%), 18C (6%), 23F (6%), 11A (6%), 34 (6%), 19F (5%) and 16 (5%). Carriage of H. influenzae and M. catarrhalis was detected in 13% (95% CI 11-15%) and 15% (95% CI 13-17%) of children, respectively. Non-susceptibility to penicillin was common among pneumococci (40%), particularly among PCV13-included serotypes (50% vs. 33%; p = 0.003), although the median minimal inhibitory concentration was low (0.19 mg/mL, IQR 0.13-0.25 mg/mL). Most pneumococci and H. influenzae were susceptible to amoxicillin (99% and 88%, respectively). Furthermore, resistance to trimethoprim-sulfamethoxazole was>70% among all three species. Multidrug-resistant pneumococci (non-susceptible to > 3 antibiotics; 7% [n = 24]) were further studied with whole genome sequencing to investigate clonality as an underlying cause for this phenotype. No clearly dominating clone(s) were, however, detected. The results indicate that continued use of PCV13 may have positive direct and herd effects on pneumococcal infections in Angola as carriage of vaccine serotypes was common in the non-vaccinated age group. Finally, amoxicillin is assessed to be a feasible empirical treatment of respiratory tract infections in Angola. (C) 2020 The Author(s). Published by Elsevier Ltd.

Identification of the etiology of childhood pneumonia is difficult, even in the cases that most likely have bacterial origins. A positive blood culture result is diagnostic but rare (50% of cases (virological tests were rarely done); (2) lung tap is safer than is generally considered; (3) potential pneumothorax is mostly symptomless and resolves spontaneously without impairing recovery; and (4) in comparison with routine diagnostic tools, lung tap offers so many advantages that it warrants reconsideration at centers where personnel have experience in handling potential pneumothorax.

The most frequent form of hemolytic-uremic syndrome (HUS) is associated with infections caused by Shiga-like toxin-producing Enterohaemorrhagic Escherichia coli (STEC). In rarer cases HUS can be triggered by Streptococcus pneumoniae. While production of Shiga-like toxins explains STEC-HUS, the mechanisms of pneumococcal HUS are less well known. S. pneumoniae produces neuraminidases with activity against cell surface sialic acids that are critical for factor H-mediated complement regulation on cells and platelets. The aim of this study was to find out whether S. pneumoniae neuraminidase NanA could trigger complement activation and hemolysis in whole blood. We studied clinical S. pneumoniae isolates and two laboratory strains, a wild-type strain expressing NanA, and a NanA deletion mutant for their ability to remove sialic acids from various human cells and platelets. Red blood cell lysis and activation of complement was measured ex vivo by incubating whole blood with bacterial culture supernatants. We show here that NanA expressing S. pneumoniae strains and isolates are able to remove sialic acids from cells, and platelets. Removal of sialic acids by NanA increased complement activity in whole blood, while absence of NanA blocked complement triggering and hemolytic activity indicating that removal of sialic acids by NanA could potentially trigger pHUS.

Background: Pneumococcus kills over one million children annually and over 90 % of these deaths occur in low-income countries especially in Sub-Saharan Africa (SSA) where HIV exacerbates the disease burden. In SSA, serotype 1 pneumococci particularly the endemic ST217 clone, causes majority of the pneumococcal disease burden. To understand the evolution of the virulent ST217 clone, we analysed ST217 whole genomes from isolates sampled from African and Asian countries. Methods: We analysed 226 whole genome sequences from the ST217 lineage sampled from 9 African and 4 Asian countries. We constructed a whole genome alignment and used it for phylogenetic and coalescent analyses. We also screened the genomes to determine presence of antibiotic resistance conferring genes. Results: Population structure analysis grouped the ST217 isolates into five sequence clusters (SCs), which were highly associated with different geographical regions and showed limited intracontinental and intercontinental spread. The SCs showed lower than expected genomic sequence, which suggested strong purifying selection and small population sizes caused by bottlenecks. Recombination rates varied between the SCs but were lower than in other successful clones such as PMEN1. African isolates showed higher prevalence of antibiotic resistance genes than Asian isolates. Interestingly, certain West African isolates harbored a defective chloramphenicol and tetracycline resistance-conferring element (Tn5253) with a deletion in the loci encoding the chloramphenicol resistance gene (cat(pC194)), which caused lower chloramphenicol than tetracycline resistance. Furthermore, certain genes that promote colonisation were absent in the isolates, which may contribute to serotype 1's rarity in carriage and consequently its lower recombination rates. Conclusions: The high phylogeographic diversity of the ST217 clone shows that this clone has been in circulation globally for a long time, which allowed its diversification and adaptation in different geographical regions. Such geographic adaptation reflects local variations in selection pressures in different locales. Further studies will be required to fully understand the biological mechanisms which makes the ST217 clone highly invasive but unable to successfully colonise the human nasopharynx for long durations which results in lower recombination rates.