Fungal Signature of Moisture Damage in Buildings: Identification by Targeted and Untargeted Approaches with Mycobiome Data.

Identifying microbial indicators of damp and moldy buildings remains a challenge at the intersection of microbiology, building science, and public health. Sixty homes in New York City were assessed for moisture-related damage, and three types of dust samples were collected for microbiological analysis. We applied four approaches for detecting fungal signatures of moisture damage in these buildings. Two novel targeted approaches selected specific taxa, identified by a priori hypotheses, from the broad mycobiome as detected with amplicon sequencing. We investigated whether (i) hydrophilic fungi (i.e., requiring high moisture) or (ii) fungi previously reported as indicating damp homes would be more abundant in water-damaged rooms/homes than in nondamaged rooms/homes. Two untargeted approaches compared water-damaged to non-water-damaged homes for (i) differences between indoor and outdoor fungal populations or (ii) differences in the presence or relative abundance of particular fungal taxa. Strong relationships with damage indicators were found for some targeted fungal groups in some sampling types, although not always in the hypothesized direction. For example, for vacuum samples, hydrophilic fungi had significantly higher relative abundance in water-damaged homes, but mesophilic fungi, unexpectedly, had significantly lower relative abundance in homes with visible mold. Untargeted approaches identified no microbial community metrics correlated with water damage variables but did identify specific taxa with at least weak positive links to water-damaged homes. These results, although showing a complex relationship between moisture damage and microbial communities, suggest that targeting particular fungi offers a potential route toward identifying a fungal signature of moisture damage in buildings.IMPORTANCE Living or working in damp or moldy buildings increases the risk of many adverse health effects, including asthma and other respiratory diseases. To date, however, the particular environmental exposure(s) from water-damaged buildings that causes the health effects have not been identified. Likewise, a consistent quantitative measurement that would indicate whether a building is water damaged or poses a health risk to occupants has not been found. In this work, we tried to develop analytical tools that would find a microbial signal of moisture damage amid the noisy background of microorganisms in buildings. The most successful approach taken here focused on particular groups of fungi-those considered likely to grow in damp indoor environments-and their associations with observed moisture damage. With further replication and refinement, this hypothesis-based strategy may be effective in finding still-elusive relationships between building damage and microbiomes.

Clonal reproduction in fungi.

Research over the past two decades shows that both recombination and clonality are likely to contribute to the reproduction of all fungi. This view of fungi is different from the historical and still commonly held view that a large fraction of fungi are exclusively clonal and that some fungi have been exclusively clonal for hundreds of millions of years. Here, we first will consider how these two historical views have changed. Then we will examine the impact on fungal research of the concept of restrained recombination [Tibayrenc M, Ayala FJ (2012) Proc Natl Acad Sci USA 109 (48):E3305-E3313]. Using animal and human pathogenic fungi, we examine extrinsic restraints on recombination associated with bottlenecks in genetic variation caused by geographic dispersal and extrinsic restraints caused by shifts in reproductive mode associated with either disease transmission or hybridization. Using species of the model yeast Saccharomyces and the model filamentous fungus Neurospora, we examine intrinsic restraints on recombination associated with mating systems that range from strictly clonal at one extreme to fully outbreeding at the other and those that lie between, including selfing and inbreeding. We also consider the effect of nomenclature on perception of reproductive mode and a means of comparing the relative impact of clonality and recombination on fungal populations. Last, we consider a recent hypothesis suggesting that fungi thought to have the most severe intrinsic constraints on recombination actually may have the fewest.

Genomic sequencing reveals historical, demographic and selective factors associated with the diversification of the fire-associated fungus Neurospora discreta.

Delineating microbial populations, discovering ecologically relevant phenotypes and identifying migrants, hybrids or admixed individuals have long proved notoriously difficult, thereby limiting our understanding of the evolutionary forces at play during the diversification of microbial species. However, recent advances in sequencing and computational methods have enabled an unbiased approach whereby incipient species and the genetic correlates of speciation can be identified by examining patterns of genomic variation within and between lineages. We present here a population genomic study of a phylogenetic species in the Neurospora discreta species complex, based on the resequencing of full genomes (~37 Mb) for 52 fungal isolates from nine sites in three continents. Population structure analyses revealed two distinct lineages in South-East Asia, and three lineages in North America/Europe with a broad longitudinal and latitudinal range and limited admixture between lineages. Genome scans for selective sweeps and comparisons of the genomic landscapes of diversity and recombination provided no support for a role of selection at linked sites on genomic heterogeneity in levels of divergence between lineages. However, demographic inference indicated that the observed genomic heterogeneity in divergence was generated by varying rates of gene flow between lineages following a period of isolation. Many putative cases of exchange of genetic material between phylogenetically divergent fungal lineages have been discovered, and our work highlights the quantitative importance of genetic exchanges between more closely related taxa to the evolution of fungal genomes. Our study also supports the role of allopatric isolation as a driver of diversification in saprobic microbes.

Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples.

Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against nasopharyngeal swab specimens and found saliva methods require further optimization to match this gold standard. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.

Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples.

Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI-FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against the gold standard, nasopharyngeal swab specimens. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.

LuNER: Multiplexed SARS-CoV-2 detection in clinical swab and wastewater samples.

Clinical and surveillance testing for the SARS-CoV-2 virus relies overwhelmingly on RT-qPCR-based diagnostics, yet several popular assays require 2-3 separate reactions or rely on detection of a single viral target, which adds significant time, cost, and risk of false-negative results. Furthermore, multiplexed RT-qPCR tests that detect at least two SARS-CoV-2 genes in a single reaction are typically not affordable for large scale clinical surveillance or adaptable to multiple PCR machines and plate layouts. We developed a RT-qPCR assay using the Luna Probe Universal One-Step RT-qPCR master mix with publicly available primers and probes to detect SARS-CoV-2 N gene, E gene, and human RNase P (LuNER) to address these shortcomings and meet the testing demands of a university campus and the local community. This cost-effective test is compatible with BioRad or Applied Biosystems qPCR machines, in 96 and 384-well formats, with or without sample pooling, and has a detection sensitivity suitable for both clinical reporting and wastewater surveillance efforts.

IGI-LuNER: single-well multiplexed RT-qPCR test for SARS-CoV-2.

Commonly used RT-qPCR-based SARS-CoV-2 diagnostics require 2-3 separate reactions or rely on detection of a single viral target, adding time and cost or risk of false-negative results. Currently, no test combines detection of widely used SARS-CoV-2 E- and N-gene targets and a sample control in a single, multiplexed reaction. We developed the IGI-LuNER RT-qPCR assay using the Luna Probe Universal One-Step RT-qPCR master mix with publicly available primers and probes to detect SARS-CoV-2 N gene, E gene, and human RNase P (NER). This combined, cost-effective test can be performed in 384-well plates with detection sensitivity suitable for clinical reporting, and will aid in future sample pooling efforts, thus improving throughput of SARS-CoV-2 detection.

A different suite: The assemblage of distinct fungal communities in water-damaged units of a poorly-maintained public housing building.

Water-damaged housing has been associated with a number of negative health outcomes, principally respiratory disease and asthma. Much of what we know about fungi associated with water-damaged buildings has come from culture-based and immunochemical methods. Few studies have used high-throughput sequencing technologies to assess the impact of water-damage on microbial communities in residential buildings. In this study we used amplicon sequencing and quantitative-PCR to evaluate fungal communities on surfaces and in airborne dust in multiple units of a condemned public housing project located in the San Francisco Bay Area. We recruited 21 households to participate in this study and characterized their apartments as either a unit with visible mold or no visible mold. We sampled airborne fungi from dust settled over a month-long time period from the outdoors, in units with no visible mold, and units with visible mold. In units with visible mold we additionally sampled the visible fungal colonies from bathrooms, kitchens, bedrooms, and living rooms. We found that fungal biomass in settled dust was greater outdoors compared to indoors, but there was no significant difference of fungal biomass in units with visible mold and no visible mold. Interestingly, we found that fungal diversity was reduced in units with visible mold compared to units with no visible mold and the outdoors. Units with visible mold harbored fungal communities distinct from units with no visible mold and the outdoors. Units with visible mold had a greater abundance of taxa within the classes Eurotiomycetes, Saccharomycetes, and Wallemiomycetes. Colonies of fungi collected from units with visible mold were dominated by two Cladosporium species, C. sphaerospermum and C halotolerans. This study demonstrates that high-throughput sequencing of fungi indoors can be a useful strategy for distinguishing distinct microbial exposures in water-damaged homes with visible and nonvisible mold growth, and may provide a microbial means for identifying water damaged housing.

Sources of Fungal Genetic Variation and Associating It with Phenotypic Diversity.

The first eukaryotic genome to be sequenced was fungal, and there continue to be more sequenced genomes in the kingdom Fungi than in any other eukaryotic kingdom. Comparison of these genomes reveals many sources of genetic variation, from single nucleotide polymorphisms to horizontal gene transfer and on to changes in the arrangement and number of chromosomes, not to mention endofungal bacteria and viruses. Population genomics shows that all sources generate variation all the time and implicate natural selection as the force maintaining genome stability. Variation in wild populations is a rich resource for associating genetic variation with phenotypic variation, whether through quantitative trait locus mapping, genome-wide association studies, or reverse ecology. Subjects of studies associating genetic and phenotypic variation include model fungi, e.g., Saccharomyces and Neurospora, but pioneering studies have also been made with fungi pathogenic to plants, e.g., Pyricularia (= Magnaporthe), Zymoseptoria, and Fusarium, and to humans, e.g., Coccidioides, Cryptococcus, and Candida.