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Specialized metabolites produced by microorganisms found in ocean sediments display a wide range of clinically relevant bioactivities, including antimicrobial, anticancer, antiviral, and anti-inflammatory. Due to limitations in our ability to culture many benthic microorganisms under laboratory conditions, their potential to produce bioactive compounds remains underexplored. However, the advent of modern mass spectrometry technologies and data analysis methods for chemical structure prediction has aided in the discovery of such metabolites from complex mixtures. In this study, ocean sediments were collected from Baffin Bay (Canadian Arctic) and the Gulf of Maine for untargeted metabolomics using mass spectrometry. A direct examination of prepared organic extracts identified 1468 spectra, of which ∼45% could be annotated using in silico analysis methods. A comparable number of spectral features were detected in sediments collected from both locations, but 16S rRNA gene sequencing revealed a significantly more diverse bacterial community in samples from Baffin Bay. Based on spectral abundance, 12 specialized metabolites known to be associated with bacteria were selected for discussion. The application of metabolomics directly on marine sediments provides an avenue for culture-independent detection of metabolites produced under natural settings. The strategy can help prioritize samples for novel bioactive metabolite discovery using traditional workflows.

The genus Protoparvovirus (family Parvoviridae) includes several viruses of carnivores. We describe a novel fox protoparvovirus, which we named Newlavirus as it was discovered in samples from Newfoundland and Labrador, Canada. Analysis of the full non-structural protein (NS1) sequence indicates that this virus is a previously uncharacterized species. Newlavirus showed high prevalence in foxes from both the mainland (Labrador, 54/137, 39.4%) and the island of Newfoundland (22/50, 44%) but was not detected in samples from other carnivores, including coyotes (n = 92), lynx (n = 58), martens (n = 146), mink (n = 47), ermines (n = 17), dogs (n = 48), and ringed (n = 4), harp (n = 6), bearded (n = 6), and harbor (n = 2) seals. Newlavirus was found at similar rates in stool and spleen (24/80, 30% vs. 59/152, 38.8%, p = 0.2) but at lower rates in lymph nodes (2/37, 5.4%, p &lt, 0.01). Sequencing a fragment of approximately 750 nt of the capsid protein gene from 53 samples showed a high frequency of co-infection by more than one strain (33.9%), high genetic diversity with 13 genotypes with low sequence identities (70.5–87.8%), and no geographic segregation of strains. Given the high prevalence, high diversity, and the lack of identification in other species, foxes are likely the natural reservoir of Newlavirus, and further studies should investigate its distribution.

High-throughput sequencing (HTS) technologies are becoming increasingly important within microbiology research, but aspects of library preparation, such as high cost per sample or strict input requirements, make HTS difficult to implement in some niche applications and for research groups on a budget. To answer these necessities, we developed ViDiT, a customizable, PCR-based, extremely low-cost (less than US$5 per sample), and versatile library preparation method, and CACTUS, an analysis pipeline designed to rely on cloud computing power to generate high-quality data from ViDiT-based experiments without the need of expensive servers. We demonstrate here the versatility and utility of these methods within three fields of microbiology: virus discovery, amplicon-based viral genome sequencing, and microbiome profiling. ViDiT–CACTUS allowed the identification of viral fragments from 25 different viral families from 36 oropharyngeal–cloacal swabs collected from wild birds, the sequencing of three almost complete genomes of avian influenza A viruses (>90% coverage), and the characterization and functional profiling of the complete microbial diversity (bacteria, archaea, viruses) within a deep-sea carnivorous sponge. ViDiT–CACTUS demonstrated its validity in a wide range of microbiology applications, and its simplicity and modularity make it easily implementable in any molecular biology laboratory, towards various research goals.

Coastal aquaculture has experienced substantial growth in the last few decades and associated impacts on natural environments are of increasing importance. Understanding both the effects of aquaculture on marine ecosystems and the processes of recovery during fallowing periods is crucial for the development of a more environmentally sustainable industry. Because bacteria are sensitive to environmental change, surveying fluctuations in bacterial communities is a promising tool for monitoring the status of benthic environments. Here, we used 16S rRNA gene high-throughput sequencing to characterize bacterial communities in flocculent matter samples collected over a period of 3 years and at various distances from cages (0–200 meters) at production and fallow (3–35 months) salmon aquaculture sites in southern Newfoundland to evaluate the environmental impact of aquaculture on predominantly hard-bottom substrates. Bacterial composition analysis revealed four clusters, three of which (defined as “recently disturbed,” “intermediate impact,” and “high impact”) differed markedly from a fourth “low impact” cluster that contained far-field samples collected >500 m from cages. Samples within the high impact group were most often collected directly under cages, whereas those in the intermediate impact group were mainly sampled from 20 to 40 m from cages. Large scale phylum shifts (increases of Bacteroidetes, Firmicutes, Spirochaetes, and decreases in Proteobacteria and Epsilonbacteraeota) and a decline in bacterial diversity were observed in the high impact cluster, indicating significant ecological change. Samples from sites of different fallow duration were found in the high impact cluster, indicating a lack of recovery, even after 35 months of fallowing. Finally, we identified 28 genera as bacterial biomarkers, specific to one or more clusters, including genera associated with organically enriched environments and previously reported in the context of aquaculture impacts. Tracking the relative abundance of biomarkers in relation to different lengths of fallowing in the three more impacted clusters showed that these markers remained significantly above low impact cluster levels at all times, further pointing toward incomplete recovery. Our results suggest that coastal aquaculture on hard-bottom substrates is prone to long lasting impacts on bacterial communities, especially below cages, and that effects can be accurately tracked using bacterial community profiles or specific biomarkers.

Acute central nervous system (CNS) infections cause substantial morbidity and mortality, but the etiology remains unknown in a large proportion of cases. We identified and characterized the full genome of a novel cyclovirus (tentatively named cyclovirus-Vietnam [CyCV-VN]) in cerebrospinal fluid (CSF) specimens of two Vietnamese patients with CNS infections of unknown etiology. CyCV-VN was subsequently detected in 4% of 642 CSF specimens from Vietnamese patients with suspected CNS infections and none of 122 CSFs from patients with noninfectious neurological disorders. Detection rates were similar in patients with CNS infections of unknown etiology and those in whom other pathogens were detected. A similar detection rate in feces from healthy children suggested food-borne or orofecal transmission routes, while high detection rates in feces from pigs and poultry (average, 58%) suggested the existence of animal reservoirs for such transmission. Further research is needed to address the epidemiology and pathogenicity of this novel, potentially zoonotic virus., IMPORTANCE Acute central nervous system (CNS) infections cause substantial morbidity and mortality, but the etiology frequently remains unknown, which hampers development of therapeutic or preventive strategies. Hence, identification of novel pathogens is essential and is facilitated by current next-generation sequencing-based methods. Using such technology, we identified and characterized the full genome of a novel cyclovirus in cerebrospinal fluid (CSF) specimens from two Vietnamese patients with CNS infections of unknown etiology, which was subsequently detected in none of 122 CSF specimens from patients with noninfectious neurological disorders but 4% of 642 CSF specimens from Vietnamese patients with suspected or confirmed CNS infections. Similar detection rates in feces from healthy children suggested food-borne or orofecal transmission routes, while frequent detection in feces from Vietnamese pigs and poultry (average, 58%) suggested the existence of animal reservoirs for such transmission. Further studies are needed to address the epidemiology and pathogenicity of this novel, potentially zoonotic virus.

Four methods for the species identification of coagulase-negative staphylococci in the medical microbiology laboratory were compared with 444 consecutive isolates. The methods included (i) the reference method based on growth tests, (ii) API ID 32 Staph (bioMérieux), (iii) Staph-Zym (Rosco), and (iv) a rapid 4-h method developed in our laboratory (UZA method). The last method is based on the detection within 4 h of enzymatic activity of heavy bacterial suspensions in three substrate solutions (nongrowth tests). For 16.5% of the isolates some supplementary growth tests read after 24 h had to be added to the enzyme data for satisfactory identification. The reference method failed to identify four isolates. Of the 440 isolates identified by the reference method, API ID 32 Staph, Staph-Zym, and the UZA method correctly identified 419 (95.2%), 429 (97.5%), and 430 (97.7%) and misidentified 8 (1.8%), 4 (0.9%), and 1 (0.2%), respectively. Staphylococcus epidermidis, S. haemolyticus, S. lugdunensis, S. schleiferi, and S. capitis were identified with an accuracy of 98 to 100% by all the systems tested. S. capitis subsp. ureolyticus was not recognized by the API ID 32 system because the biochemical profiles for it are not yet included in the corresponding database. Whereas API ID 32 identified all 13 S. warneri isolates, both Staph-Zym and the UZA method missed 2 of these. S. hominis was identified with the least accuracy by the API ID 32 system (26 of 39 isolates), whereas the UZA and Staph-Zym methods identified 36 of the isolates belonging to this species. The UZA method did not identify any of the S. cohnii, S. xylosus, S. lentus, and S. sciuri strains, since it included no discriminatory tests for these species, because they are extremely rarely found in humans. Of all 440 isolates tested, the UZA method failed to identify 9 and misidentified 1 other. Eighty-one percent of the isolates were identified within 4 h and 97.7% were identified after 24 h, at considerably less expense than by the API ID 32 Staph and Staph-Zym methods.

A commercially available fluorescence test (Crystal MRSA ID System; BBL) for the rapid detection of methicillin resistance in Staphylococcus aureus was evaluated for the detection of methicillin resistance in coagulase-negative staphylococci. The assay was compared with the agar dilution method and mecA detection by PCR. Provided that one uses an inoculum equivalent to a no. 2 McFarland standard instead of a no. 0.5 McFarland standard, which is used for S. aureus, the Crystal MRSA ID System detects methicillin resistance among coagulase-negative staphylococci with sensitivity, specificity, and positive and negative predictive values of 98.5, 95.4, 96.3, and 98.1%, respectively.

We describe a patient with a serious urinary tract infection due to Actinomyces bernardiae (formerly classified as CDC [Centers for Disease Control and Prevention, Atlanta] fermentative coryneform group 2). Our patient had long-standing bladder dysfunction and developed hydroureteronephrosis, renal lithiasis, perirenal abscesses, and septicemia. A. bernardiae is distinct from Actinomyces pyogenes and several CDC coryneform groups.