Characterisation of Staphylococci species from neonatal blood cultures in low- and middle-income countries

Abstract

Background: In low- and middle-income countries (LMIC) Staphylococcus aureus is regarded as one of the leading bacterial causes of neonatal sepsis, however there is limited knowledge on the species diversity and antimicrobial resistance caused by Gram-positive bacteria (GPB).

Methods: We characterised GPB isolates from neonatal blood cultures from LMICs in Africa (Ethiopia, Nigeria, Rwanda, and South Africa) and South-Asia (Bangladesh and Pakistan) between 2015-2017. We determined minimum inhibitory concentrations and performed whole genome sequencing (WGS) on Staphylococci isolates recovered and clinical data collected related to the onset of sepsis and the outcome of the neonate up to 60 days of age.

Results: From the isolates recovered from blood cultures, Staphylococci species were most frequently identified. Out of 100 S. aureus isolates sequenced, 18 different sequence types (ST) were found which unveiled two small epidemiological clusters caused by methicillin resistant S. aureus (MRSA) in Pakistan (ST8) and South Africa (ST5), both with high mortality (n = 6/17). One-third of S. aureus was MRSA, with methicillin resistance also detected in Staphylococcus epidermidis, Staphylococcus haemolyticus and Mammaliicoccus sciuri. Through additional WGS analysis we report a cluster of M. sciuri in Pakistan identified between July-November 2017.

Conclusions: In total we identified 14 different GPB bacterial species, however Staphylococci was dominant. These findings highlight the need of a prospective genomic epidemiology study to comprehensively assess the true burden of GPB neonatal sepsis focusing specifically on mechanisms of resistance and virulence across species and in relation to neonatal outcome.

Keywords: Early onset; Epidemiology; Genomics; LMIC; Late onset; Mammaliicocci; Mortality; Neonatal sepsis; Staphylococci.

Fig. 1

Core genome phylogenetic analysis of Staphylococcus aureus including a global contextual analysis. a Detailed core genome characterisation of 100 Staphylococcus aureus isolates (BARNARDS) using Roary (v3.12.0) and Fasttree (v2.1.11). Isolate labels are coloured according to clinical site of origin. The in-silico sequence type (ST) is shown outside of the isolate code (leaf). Presence of mecA, and whether the isolate was classified phenotypically as MRSA (as inferred from oxacillin MIC > 2 mg/l) is denoted by a filled triangle and/or circle respectively. Presence of IS256 is denoted by a filled rectangle. b Core genome characterisation of 351 Staphylococcus aureus isolates, incorporating a European collection [29] using Roary (v3.12.0) and Fasttree (v2.1.11). Coloured ranges in blue represent a S. aureus from the BARNARDS collection. Branch labels are coloured according to country of origin. Symbol represents source of isolate

Fig. 2

Core genome phylogenetic analysis of coagulase negative Staphylococcus blood culture isolates. Core genome phylogeny of CoNS isolates displaying key genomic traits for comparison using Roary (v3.12.0) and Fasttree (v2.1.11). Isolate labels are coloured according to clinical site of origin. Clades are highlighted according to species. The in-silico sequence type (ST) is shown outside of the isolate code (leaf). Presence of mecA, and whether the isolate was classified phenotypically as MRSA (as inferred from oxacillin MIC > 2 mg/l) is denoted by a filled triangle and/or circle respectively. Presence of IS256 is denoted by a filled rectangle

Fig. 3

Temporal frequency and survival curve data for Staphylococcus aureus blood culture isolates. a Stacked bar graph to show the temporal frequency of S. aureus isolates recovered from blood cultures during the BARNARDS sampling, per month. The bar graph is coloured according to the dominant STs, with all other STs being grouped as ‘Other’. b A Kaplan Meier survival plot comparing the four dominant ST groups (with all other STs detected grouped together as a single group called ‘other’) against the age at outcome for the neonate and up to 60 days. Findings are suggestive as the data presented is from a sample size (ST152 n = 15, ST other n = 37, ST5 n = 17, ST6 n = 18 and ST8 n = 13; overall comparison P 0.041)

Fig. 4

Neonatal survival curve data for Staphylococcus aureus and pathogenicity markers: MRSA and PVL. Kaplan Meier survival plot comparing a MRSA v MSSA and time to neonatal outcome, and b The presence of virulence factor PVL and time to neonatal outcome censored at the last available follow up appointment

Fig. 5

a Analysis of Mammaliicoccus sciuri recovered from blood cultures and a WGS contextual analysis. A timeline of M. sciuri neonatal sepsis in Pakistan, indicating which were available for whole genome characterisation. The blocks represent an individual case, and are colour coded according to the clinical outcome of sepsis. b A core genome SNP tree for all PP-BB isolates with WGS data available, performed using snippy-gubbins and Raxml (please refer to the text for details on methods) c Comparative phylogenetic tree of all S. sciuri with WGS data available in BARNARDS including the 10 genetically closest strains of M. sciuri from NCBI