Genomic characterization and assessment of pathogenic potential of Legionella spp. isolates from environmental monitoring.

Several species in the genus Legionella are known to cause an acute pneumonia when the aerosols containing the bacteria from man-made water systems are inhaled. The disease is usually caused by Legionella pneumophila, but other species have been implicated in the infection. The disease is frequently manifested as an outbreak, which means several people are affected when exposed to the common source of Legionella contamination. Therefor environmental surveillance which includes isolation and identification of Legionella is performed routinely. However, usually no molecular or genome-based methods are employed in further characterization of the isolates during routine environmental monitoring. During several years of such monitoring, isolates from different geographical locations were collected and 39 of them were sequenced by hybrid de novo approach utilizing short and long sequencing reads. In addition, the isolates were typed by standard culture and MALDI-TOF method. The sequencing reads were assembled and annotated to produce high-quality genomes. By employing discriminatory genome typing, four potential new species in the Legionella genus were identified, which are yet to be biochemically and morphologically characterized. Moreover, functional annotations concerning virulence and antimicrobial resistance were performed on the sequenced genomes. The study contributes to the knowledge on little-known non-pneumophila species present in man-made water systems and establishes support for future genetic relatedness studies as well as understanding of their pathogenic potential.

A New Animal Model of Insulin-Glucose Dynamics in the Intraperitoneal Space Enhances Closed-Loop Control Performance.

Current artificial pancreas systems (AP) operate via subcutaneous (SC) glucose sensing and SC insulin delivery. Due to slow diffusion and transport dynamics across the interstitial space, even the most sophisticated control algorithms in on-body AP systems cannot react fast enough to maintain tight glycemic control under the effect of exogenous glucose disturbances caused by ingesting meals or performing physical activity. Recent efforts made towards the development of an implantable AP have explored the utility of insulin infusion in the intraperitoneal (IP) space: a region within the abdominal cavity where the insulin-glucose kinetics are observed to be much more rapid than the SC space. In this paper, a series of canine experiments are used to determine the dynamic association between IP insulin boluses and plasma glucose levels. Data from these experiments are employed to construct a new mathematical model and to formulate a closed-loop control strategy to be deployed on an implantable AP. The potential of the proposed controller is demonstrated via in-silico experiments on an FDA-accepted benchmark cohort: the proposed design significantly outperforms a previous controller designed using artificial data (time in clinically acceptable glucose range: 97.3±1.5% vs. 90.1±5.6%). Furthermore, the robustness of the proposed closed-loop system to delays and noise in the measurement signal (for example, when glucose is sensed subcutaneously) and deleterious glycemic changes (such as sudden glucose decline due to physical activity) is investigated. The proposed model based on experimental canine data leads to the generation of more effective control algorithms and is a promising step towards fully automated and implantable artificial pancreas systems.

Effects of holding time and measurement error on culturing Legionella in environmental water samples.

Outbreaks of Legionnaires' disease require environmental testing of water samples from potentially implicated building water systems to identify the source of exposure. A previous study reports a large impact on Legionella sample results due to shipping and delays in sample processing. Specifically, this same study, without accounting for measurement error, reports more than half of shipped samples tested had Legionella levels that arbitrarily changed up or down by one or more logs, and the authors attribute this result to shipping time. Accordingly, we conducted a study to determine the effects of sample holding/shipping time on Legionella sample results while taking into account measurement error, which has previously not been addressed. We analyzed 159 samples, each split into 16 aliquots, of which one-half (8) were processed promptly after collection. The remaining half (8) were processed the following day to assess impact of holding/shipping time. A total of 2544 samples were analyzed including replicates. After accounting for inherent measurement error, we found that the effect of holding time on observed Legionella counts was small and should have no practical impact on interpretation of results. Holding samples increased the root mean squared error by only about 3-8%. Notably, for only one of 159 samples, did the average of the 8 replicate counts change by 1 log. Thus, our findings do not support the hypothesis of frequent, significant (≥= 1 log10 unit) Legionella colony count changes due to holding.

Distribution of lag-1 alleles and sequence-based types among Legionella pneumophila serogroup 1 clinical and environmental isolates in the United States.

Approximately 84% of legionellosis cases are due to Legionella pneumophila serogroup 1. Moreover, a majority of L. pneumophila serogroup 1 clinical isolates react positively with monoclonal antibody 2 (MAb2) of the international standard panel. Over 94% of the legionellosis outbreaks investigated by the Centers for Disease Control and Prevention are due to this subset of L. pneumophila serogroup 1. To date, there is no complete explanation for the enhanced ability of these strains to cause disease. To better characterize these organisms, we subtyped 100 clinical L. pneumophila serogroup 1 isolates and 50 environmental L. pneumophila serogroup 1 isolates from the United States by (i) reactivity with MAb2, (ii) presence of a lag-1 gene required for the MAb2 epitope, and (iii) sequence-based typing analysis. Our results showed that the MAb2 epitope and lag-1 gene are overrepresented in clinical L. pneumophila serogroup 1 isolates. MAb2 recognized 75% of clinical isolates but only 6% of environmental isolates. Similarly, 75% of clinical isolates but only 8% of environmental isolates harbored lag-1. We identified three distinct lag-1 alleles, referred to as Philadelphia, Arizona, and Lens alleles, among 79 isolates carrying this gene. The Arizona allele is described for the first time in this study. We identified 59 different sequence types (STs), and 34 STs (58%) were unique to the United States. Our results support the hypothesis that a select group of STs may have an enhanced ability to cause legionellosis. Combining sequence typing and lag-1 analysis shows that STs tend to associate with a single lag-1 allele type, suggesting a hierarchy of virulence genotypes. Further analysis of ST and lag-1 profiles may identify genotypes of L. pneumophila serogroup 1 that warrant immediate intervention.

Profiles of airborne fungi in buildings and outdoor environments in the United States.

We examined 12,026 fungal air samples (9,619 indoor samples and 2,407 outdoor samples) from 1,717 buildings located across the United States; these samples were collected during indoor air quality investigations performed from 1996 to 1998. For all buildings, both indoor and outdoor air samples were collected with an Andersen N6 sampler. The culturable airborne fungal concentrations in indoor air were lower than those in outdoor air. The fungal levels were highest in the fall and summer and lowest in the winter and spring. Geographically, the highest fungal levels were found in the Southwest, Far West, and Southeast. The most common culturable airborne fungi, both indoors and outdoors and in all seasons and regions, were Cladosporium, Penicillium, nonsporulating fungi, and Aspergillus. Stachybotrys chartarum was identified in the indoor air in 6% of the buildings studied and in the outdoor air of 1% of the buildings studied. This study provides industrial hygienists, allergists, and other public health practitioners with comparative information on common culturable airborne fungi in the United States. This is the largest study of airborne indoor and outdoor fungal species and concentrations conducted with a standardized protocol to date.