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Cooling towers (CTs) are a leading source of outbreaks of Legionnaires' disease (LD), a severe form of pneumonia caused by inhalation of aerosols containing Legionella bacteria. Accordingly, proper maintenance of CTs is vital for the prevention of LD. The aim of this study was to determine the distribution of Legionella in a subset of regionally diverse US CTs and characterize the associated microbial communities. Between July and September of 2016, we obtained aliquots from water samples collected for routine Legionella testing from 196 CTs located in eight of the nine continental US climate regions. After screening for Legionella by PCR, positive samples were cultured and the resulting Legionella isolates were further characterized. Overall, 84% (164) were PCR-positive, including samples from every region studied. Of the PCR-positive samples, Legionella spp were isolated from 47% (78), L. pneumophila was isolated from 32% (53), and L. pneumophila serogroup 1 (Lp1) was isolated from 24% (40). Overall, 144 unique Legionella isolates were identified; 53% (76) of these were Legionella pneumophila. Of the 76 L. pneumophila isolates, 51% (39) were Lp1. Legionella were isolated from CTs in seven of the eight US regions examined. 16S rRNA amplicon sequencing was used to compare the bacterial communities of CT waters with and without detectable Legionella as well as the microbiomes of waters from different climate regions. Interestingly, the microbial communities were homogenous across climate regions. When a subset of seven CTs sampled in April and July were compared, there was no association with changes in corresponding CT microbiomes over time in the samples that became culture-positive for Legionella. Legionella species and Lp1 were detected frequently among the samples examined in this first large-scale study of Legionella in US CTs. Our findings highlight that, under the right conditions, there is the potential for CT-related LD outbreaks to occur throughout the US.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019, and the outbreak rapidly evolved into the current coronavirus disease pandemic. SARS-CoV-2 is a respiratory virus that causes symptoms similar to those caused by influenza A and B viruses. On July 2, 2020, the US Food and Drug Administration granted emergency use authorization for in vitro diagnostic use of the Influenza SARS-CoV-2 Multiplex Assay. This assay detects influenza A virus at 102.0, influenza B virus at 102.2, and SARS-CoV-2 at 100.3 50% tissue culture or egg infectious dose, or as few as 5 RNA copies/reaction. The simultaneous detection and differentiation of these 3 major pathogens increases overall testing capacity, conserves resources, identifies co-infections, and enables efficient surveillance of influenza viruses and SARS-CoV-2.

Mycoplasma pneumoniae is a significant cause of respiratory illness worldwide. Despite a minimal and highly conserved genome, genetic diversity within the species may impact disease. We performed whole genome sequencing (WGS) analysis of 107 M. pneumoniae isolates, including 67 newly sequenced using the Pacific BioSciences RS II and/or Illumina MiSeq sequencing platforms. Comparative genomic analysis of 107 genomes revealed >3,000 single nucleotide polymorphisms (SNPs) in total, including 520 type-specific SNPs. Population structure analysis supported the existence of six distinct subgroups, three within each type. We developed a predictive model to classify an isolate based on whole genome SNPs called against the reference genome into the identified subtypes, obviating the need for genome assembly. This study is the most comprehensive WGS analysis for M. pneumoniae to date, underscoring the power of combining complementary sequencing technologies to overcome difficult-to-sequence regions and highlighting potential differential genomic signatures in M. pneumoniae.

Infectious disease nucleic acid amplification technologies (NAAT) have superior sensitivity, specificity, and rapid time to result compared to traditional microbiological methods. Recovery of concentrated, high quality pathogen nucleic acid (NA) from complex specimen matrices is required for optimal performance of several NA amplification/detection technologies such as polymerase chain reaction (PCR). Fully integrated NAAT platforms that enable rapid sample-to-result workflows with minimal user input are generally restricted to larger reference lab settings, and their complexity and cost are prohibitive to widespread implementation in resource limited settings (RLS). Identification of component technologies for incorporation of reliable and affordable sample preparation with pathogen NA amplification/detection into an integrated platform suitable for RLS, is a necessary first step toward achieving the overarching goal of reducing infectious disease-associated morbidity and mortality globally. In the current study, we evaluate the performance of six novel NA extraction technologies from different developers using blinded panels of stool, sputum and blood spiked with variable amounts of quality-controlled DNA- and/or RNA-based microbes. The extraction efficiencies were semi-quantitatively assessed using validated real-time reverse transcription (RT)-PCR assays specific for each microbe and comparing target-specific RT-PCR results to those obtained with reference NA extraction methods. The technologies were ranked based on overall diagnostic accuracy (analytical sensitivity and specificity). Sample input and output volumes, total processing time, user-required manual steps and cost estimates were also examined for suitability in RLS. Together with the performance analysis, these metrics were used to select the more suitable candidate technologies for further optimization of integrated NA amplification and detection technologies for RLS.

Globally, over 400,000 neonatal deaths in 2015 were attributed to sepsis, however, the incidence and etiologies of these infections are largely unknown in low-middle income countries. We aimed to determine incidence and etiology of community-acquired early-onset (<72 hours age) sepsis (EOS) using culture and molecular diagnostics. This was a prospective observational study, in which we conducted a surveillance for pathogens using a combination of blood culture and a polymerase chain reaction (PCR)-based test. Blood culture was performed on all neonates with suspected EOS. Among the subset fulfilling criteria for protocol-defined EOS, blood and nasopharyngeal (NP) respiratory swabs were tested by quantitative real-time reverse-transcriptase PCR using a Taqman Array Card (TAC) with 15 bacterial and 12 viral targets. Blood and NP samples from 312 healthy newborns were also tested by TAC to estimate background positivity rates. We used variant latent-class methods to attribute etiologies and calculate pathogen-specific proportions and incidence rates. We enrolled 2,624 neonates with suspected EOS and from these 1,231 newborns met criteria for protocol-defined EOS (incidence- 39.3/1,000 live-births). Using the partially latent-class modelling, only 26.7% cases with protocol-defined EOS had attributable etiology, and the largest pathogen proportion were Ureaplasma spp. (5.4%; 95%CI: 3.6-8.0) and group B Streptococcus (GBS) (4.8%; 95%CI: 4.1-5.8), and no etiology was attributable for 73.3% of cases. Blood cultures were positive in 99/1,231 (8.0%) with protocol-defined EOS (incidence- 3.2/1,000 live-births). Leading pathogens on blood culture included GBS (35%) and viridans streptococci (24%). Ureaplasma spp. was the most common organism identified on TAC among cases with protocol-defined EOS. Using a combination of blood culture and a PCR-based test the common pathogens isolated in neonates with sepsis were Ureaplasma spp. and GBS. Despite documenting higher rates of protocol-defined EOS and using a combination of tests, the etiology for EOS remains elusive.

Legionella pneumophila was first recognized as a cause of severe and potentially fatal pneumonia during a large-scale outbreak of Legionnaires' disease (LD) at a Pennsylvania veterans' convention in Philadelphia, 1976. The ensuing investigation and recovery of four clinical isolates launched the fields of Legionella epidemiology and scientific research. Only one of the original isolates, \"Philadelphia-1\", has been widely distributed or extensively studied. Here we describe the whole-genome sequencing (WGS), complete assembly, and comparative analysis of all Philadelphia LD strains recovered from that investigation, along with L. pneumophila isolates sharing the Philadelphia sequence type (ST36). Analyses revealed that the 1976 outbreak was due to multiple serogroup 1 strains within the same genetic lineage, differentiated by an actively mobilized, self-replicating episome that is shared with L. pneumophila str. Paris, and two large, horizontally-transferred genomic loci, among other polymorphisms. We also found a completely unassociated ST36 strain that displayed remarkable genetic similarity to the historical Philadelphia isolates. This similar strain implies the presence of a potential clonal population, and suggests important implications may exist for considering epidemiological context when interpreting phylogenetic relationships among outbreak-associated isolates. Additional extensive archival research identified the Philadelphia isolate associated with a non-Legionnaire case of \"Broad Street pneumonia\", and provided new historical and genetic insights into the 1976 epidemic. This retrospective analysis has underscored the utility of fully-assembled WGS data for Legionella outbreak investigations, highlighting the increased resolution that comes from long-read sequencing and a sequence type-matched genomic data set.

Legionella spp. are the cause of a severe bacterial pneumonia known as Legionnaires' disease (LD). In some cases, current genetic subtyping methods cannot resolve LD outbreaks caused by common, potentially endemic L. pneumophila (Lp) sequence types (ST), which complicates laboratory investigations and environmental source attribution. In the United States (US), ST1 is the most prevalent clinical and environmental Lp sequence type. In order to characterize the ST1 population, we sequenced 289 outbreak and non-outbreak associated clinical and environmental ST1 and ST1-variant Lp strains from the US and, together with international isolate sequences, explored their genetic and geographic diversity. The ST1 population was highly conserved at the nucleotide level; 98% of core nucleotide positions were invariant and environmental isolates unassociated with human disease (n = 99) contained ~65% more nucleotide diversity compared to clinical-sporadic (n = 139) or outbreak-associated (n = 28) ST1 subgroups. The accessory pangenome of environmental isolates was also ~30-60% larger than other subgroups and was enriched for transposition and conjugative transfer-associated elements. Up to ~10% of US ST1 genetic variation could be explained by geographic origin, but considerable genetic conservation existed among strains isolated from geographically distant states and from different decades. These findings provide new insight into the ST1 population structure and establish a foundation for interpreting genetic relationships among ST1 strains; these data may also inform future analyses for improved outbreak investigations.

Identification of etiology remains a significant challenge in the diagnosis of infectious diseases, particularly in resource-poor settings. Viral, bacterial, and fungal pathogens, as well as parasites, play a role for many syndromes, and optimizing a single diagnostic system to detect a range of pathogens is challenging. The TaqMan Array Card (TAC) is a multiple-pathogen detection method that has previously been identified as a valuable technique for determining etiology of infections and holds promise for expanded use in clinical microbiology laboratories and surveillance studies. We selected TAC for use in the Aetiology of Neonatal Infection in South Asia (ANISA) study for identifying etiologies of severe disease in neonates in Bangladesh, India, and Pakistan. Here we report optimization of TAC to improve pathogen detection and overcome technical challenges associated with use of this technology in a large-scale surveillance study. Specifically, we increased the number of assay replicates, implemented a more robust RT-qPCR enzyme formulation, and adopted a more efficient method for extraction of total nucleic acid from blood specimens. We also report the development and analytical validation of ten new assays for use in the ANISA study. Based on these data, we revised the study-specific TACs for detection of 22 pathogens in NP/OP swabs and 12 pathogens in blood specimens as well as two control reactions (internal positive control and human nucleic acid control) for each specimen type. The cumulative improvements realized through these optimization studies will benefit ANISA and perhaps other studies utilizing multiple-pathogen detection approaches. These lessons may also contribute to the expansion of TAC technology to the clinical setting.

Mycoplasma pneumoniae is a cell wall-less bacterial pathogen of the human respiratory tract that accounts for > 20% of all community-acquired pneumonia (CAP). At present the most effective means for detection and strain-typing is quantitative polymerase chain reaction (qPCR), which can exhibit excellent sensitivity and specificity but requires separate tests for detection and genotyping, lacks standardization between available tests and between labs, and has limited practicality for widespread, point-of-care use. We have developed and previously described a silver nanorod array-surface enhanced Raman Spectroscopy (NA-SERS) biosensing platform capable of detecting M. pneumoniae with statistically significant specificity and sensitivity in simulated and true clinical throat swab samples, and the ability to distinguish between reference strains of the two main genotypes of M. pneumoniae. Furthermore, we have established a qualitative lower endpoint of detection for NA-SERS of < 1 genome equivalent (cell/μl) and a quantitative multivariate detection limit of 5.3 ± 1 cells/μl. Here we demonstrate using partial least squares- discriminatory analysis (PLS-DA) of sample spectra that NA-SERS correctly identified M. pneumoniae clinical isolates from globally diverse origins and distinguished these from a panel of 12 other human commensal and pathogenic mycoplasma species with 100% cross-validated statistical accuracy. Furthermore, PLS-DA correctly classified by strain type all 30 clinical isolates with 96% cross-validated accuracy for type 1 strains, 98% cross-validated accuracy for type 2 strains, and 90% cross-validated accuracy for type 2V strains.

Background.Mycoplasma pneumoniae continues to be a significant cause of community-acquired pneumonia (CAP). A more definitive methodology for reliable detection of M. pneumoniae is needed to identify outbreaks and to prevent potentially fatal extrapulmonary complications. Methods.We analyzed 2 outbreaks of CAP due to M. pneumoniae. Nasopharyngeal and/or oropharyngeal swab specimens and serum samples were obtained from persons with clinically defined cases, household contacts, and asymptomatic individuals. Real-time polymerase chain reaction (PCR) for M. pneumoniae was performed on all swab specimens, and the diagnostic utility was compared with that of 2 commercially available serologic test kits. Results.For cases, 21% yielded positive results with real-time PCR, whereas 81% and 54% yielded positive results with the immunoglobulin M and immunoglobulin G/immunoglobulin M serologic tests, respectively. For noncases, 1.8% yielded positive results with real-time PCR, whereas 63% and 79% yielded serologically positive results with the immunoglobulin M and immunoglobulin G/immunoglobulin M kits, respectively. The sensitivity of real-time PCR decreased as the duration between symptom onset and sample collection increased, with a peak sensitivity of 48% at 0–21 days. A specificity of 43% for the immunoglobulin M antibody detection assay was observed for persons aged 10–18 years, but the sensitivity increased to 82% for persons aged ⩾19 years. Discussion.Thorough data analysis indicated that no single available test was reliable for the identification of an outbreak of CAP due to M. pneumoniae. A combination of testing methodologies proved to be the most reliable approach for identification of outbreaks of CAP due to M. pneumoniae, especially in the absence of other suspected respiratory pathogens.