Context-specific synthetic T cell promoters from assembled transcriptional elements.

Genetic engineering of human lymphocytes for therapeutic applications is constrained by a lack of transgene transcriptional control, resulting in a compromised therapeutic index. Incomplete understanding of transcriptional logic limits the rational design of contextually responsive genetic modules1. Here, we juxtaposed rationally curated transcriptional response element (TRE) oligonucleotides by random concatemerization to generate a library from which we selected context-specific inducible synthetic promoters (iSynPros). Through functional selection, we screened an iSynPro library for "IF-THEN" logic-gated transcriptional responses in human CD8+ T cells expressing a 4-1BB second generation chimeric antigen receptor (CAR). iSynPros exhibiting stringent off-states in quiescent T cells and CAR activation-dependent transcriptional responsiveness were cloned and subjected to TRE composition and pattern analysis, as well as performance in regulating candidate antitumor potency enhancement modules. These data reveal synthetic TRE grammar can mediate logic-gated transgene transcription in human T cells that, when applied to CAR T cell engineering, enhance potency and improve therapeutic indices.

Sleep Measurement Using Wrist-Worn Accelerometer Data Compared with Polysomnography.

This study determined if using alternative sleep onset (SO) definitions impacted accelerometer-derived sleep estimates compared with polysomnography (PSG). Nineteen participants (48%F) completed a 48 h visit in a home simulation laboratory. Sleep characteristics were calculated from the second night by PSG and a wrist-worn ActiGraph GT3X+ (AG). Criterion sleep measures included PSG-derived Total Sleep Time (TST), Sleep Onset Latency (SOL), Wake After Sleep Onset (WASO), Sleep Efficiency (SE), and Efficiency Once Asleep (SE_ASLEEP). Analogous variables were derived from temporally aligned AG data using the Cole-Kripke algorithm. For PSG, SO was defined as the first score of 'sleep'. For AG, SO was defined three ways: 1-, 5-, and 10-consecutive minutes of 'sleep'. Agreement statistics and linear mixed effects regression models were used to analyze 'Device' and 'Sleep Onset Rule' main effects and interactions. Sleep-wake agreement and sensitivity for all AG methods were high (89.0-89.5% and 97.2%, respectively); specificity was low (23.6-25.1%). There were no significant interactions or main effects of 'Sleep Onset Rule' for any variable. The AG underestimated SOL (19.7 min) and WASO (6.5 min), and overestimated TST (26.2 min), SE (6.5%), and SE_ASLEEP (1.9%). Future research should focus on developing sleep-wake detection algorithms and incorporating biometric signals (e.g., heart rate).

Prevalence of Field-Collected House Flies and Stable Flies With Bacteria Displaying Cefotaxime and Multidrug Resistance.

Antibiotic use in livestock accounts for 80% of total antibiotic use in the United States and has been described as the driver for resistance evolution and spread. As clinical infections with multidrug-resistant pathogens are rapidly rising, there remains a missing link between agricultural antibiotic use and its impact on human health. In this study, two species of filth flies from a livestock operation were collected over the course of 11 mo: house flies Musca domestica (L.) (Diptera: Muscidae), representing a generalist feeder, and stable flies Stomoxys calcitrans (L.) (Diptera: Muscidae), representing a specialist (blood) feeder. The prevalence of flies carrying cefotaxime-resistant (CTX-R) bacteria in whole bodies and dissected guts were assayed by culturing on antibiotic-selective media, with distinct colonies identified by Sanger sequencing. Of the 149 flies processed, including 81 house flies and 68 stable flies, 18 isolates of 12 unique bacterial species resistant to high-level cefotaxime were recovered. These isolates also showed resistance to multiple classes of antibiotics. The CTX-R isolates were predominantly recovered from female flies, which bore at least two resistant bacterial species. The majority of resistant bacteria were isolated from the guts encompassing both enteric pathogens and commensals, sharing no overlap between the two fly species. Together, we conclude that house flies and stable flies in the field could harbor multidrug-resistant bacteria. The fly gut may serve as a reservoir for the acquisition and dissemination of resistance genes.

Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Time of day, but not sleep restriction, affects markers of hemostasis following heavy exercise.

We sought to determine the effects of sleep restriction on markers of hemostasis the morning after an exercise session. Seven subjects performed evening exercise followed by an exercise session the next morning, both with and without sleep restriction. Evening exercise included a 20-min submaximal cycling trial (10 min at 50% maximal power (Wmax), 10 min at 60% Wmax), a 3-km cycling time trial, 60 min of cycling intervals, and 3 sets of leg press. Subsequent morning exercise was the same, excluding intervals and leg press. Blood samples were collected at rest and following the 20-min submaximal trial for factor VIII antigen, tissue plasminogen activator (tPA) activity, and plasminogen activator inhibitor-1 (PAI-1) activity. Sleep restriction had no effect on the variables. Factor VIII antigen was higher and tPA activity lower in the morning versus evening, respectively (P < 0.05). There were larger (P < 0.05) exercise responses for tPA activity in the evening (pre-exercise = 0.32 ± 0.14, postexercise = 1.89 ± 0.60 AU/mL) versus morning (pre-exercise = 0.27 ± 0.13 AU/mL, postexercise = 0.69 ± 0.18 AU/mL). PAI-1 exhibited lower (P < 0.05) responses in the evening (pre-exercise = 0.78 ± 0.26 AU/mL, postexercise = 0.69 ± 0.29 AU/mL) versus morning (pre-exercise = 7.06 ± 2.66, postexercise = 5.40 ± 2.31 AU/mL). Although a prothrombotic environment was observed the morning following an evening exercise session, it was not exacerbated by sleep restriction.

Quadriceps Lipid Content Has Sex-Specific Associations With Whole-Muscle, Cellular, and Molecular Contractile Function in Older Adults.

Increased adiposity is associated with reduced skeletal muscle function in older adults, but the mechanisms underlying this relationship remain unclear. To explore whether skeletal muscle properties track with adiposity, whole-muscle, cellular, and molecular function were examined in relation to adiposity measured at various anatomical levels in healthy older (60-80 years) men and women. Although women had greater absolute and relative body and thigh fat than men, quadriceps muscle attenuation, an index of intramuscular lipid content, was similar between sexes. At the whole-muscle level, greater quadriceps attenuation was associated with reduced knee extensor function in women, but not men. In women, decreased myosin heavy chain I and IIA fiber-specific force was associated with higher intramuscular lipid content, which may be explained, in part, by the reduced myofilament lattice stiffness found in myosin heavy chain IIA fibers. Longer myosin attachment times in myosin heavy chain I fibers from men and women were associated with greater amounts of adipose tissue, suggesting that fat deposits lead to slower myosin-actin cross-bridge kinetics. Our results indicate greater quantities of adipose tissue alter myofilament properties and cross-bridge kinetics, which may partially explain the adiposity-induced decrements in single-fiber and whole-muscle function of older adults, especially women.

One night of sleep restriction following heavy exercise impairs 3-km cycling time-trial performance in the morning.

The goal of this project was to examine the influence of a single night of sleep restriction following heavy exercise on cycling time-trial (TT) performance and skeletal muscle function in the morning. Seven recreational cyclists (age, 24 ± 7 years; peak oxygen consumption, 62 ± 4 mL·kg-1·min-1) completed 2 phases, each comprising evening (EX1) and next-morning (EX2) exercise sessions. EX1 and EX2 were separated by an assigned sleep condition: a full night of rest (CON; 7.1 ± 0.3 h of sleep) or sleep restriction through early waking (SR; 2.4 ± 0.2 h). EX1 comprised baseline testing (muscle soreness, isokinetic torque, and 3-km TT performance) followed by heavy exercise that included 60 min of high-intensity cycling intervals and resistance exercise. EX2 was performed to assess recovery from EX1 and included all baseline measures. Magnitude-based inferences were used to evaluate all variables. SR had a negative effect (very likely) on the change in 3-km TT performance compared with CON. Specifically, 3-km TT performance was 'very likely' slower during EX2 compared with EX1 following SR (-4.0% ± 3.0%), whereas 3-km TT performance was 'possibly' slower during EX2 (vs. EX1) following CON (-0.5% ± 3.0%). Sleep condition did not influence changes in peak torque or muscle soreness from EX1 to EX2. A single night of sleep restriction following heavy exercise had marked consequences on 3-km TT performance the next morning. Because occasional sleep loss is likely, strategies to ameliorate the consequences of sleep loss on performance should be investigated.

Structure/property comparisons of chemistries based on renewable 1,3-propanediol and petroleum-derived alkylene oxides.

Structure/property comparisons were made of chemistries based on renewable 1,3-propanediol (PDO)- versus petroleum-based alkylene oxides as well as comparisons of the respective polyethers, emulsifiers, and cosmetic formulations based on these feedstocks. Green Chemistry Principles were applied in the manufacture of polyethylene glycol (PEG)-free renewable PDO-based oligomers and PDO-based fatty acid ester emulsifiers. Sustainable cosmetic products formulated with renewable PDO-based emulsifiers gave equivalent performance in sensory and moisturization evaluations compared to those formulated with the petroleum-derived PEG-based emulsifiers.

cual-id: Globally Unique, Correctable, and Human-Friendly Sample Identifiers for Comparative Omics Studies.

The number of samples in high-throughput comparative "omics" studies is increasing rapidly due to declining experimental costs. To keep sample data and metadata manageable and to ensure the integrity of scientific results as the scale of these projects continues to increase, it is essential that we transition to better-designed sample identifiers. Ideally, sample identifiers should be globally unique across projects, project teams, and institutions; short (to facilitate manual transcription); correctable with respect to common types of transcription errors; opaque, meaning that they do not contain information about the samples; and compatible with existing standards. We present cual-id, a lightweight command line tool that creates, or mints, sample identifiers that meet these criteria without reliance on centralized infrastructure. cual-id allows users to assign universally unique identifiers, or UUIDs, that are globally unique to their samples. UUIDs are too long to be conveniently written on sampling materials, such as swabs or microcentrifuge tubes, however, so cual-id additionally generates human-friendly 4- to 12-character identifiers that map to their UUIDs and are unique within a project. By convention, we use "cual-id" to refer to the software, "CualID" to refer to the short, human-friendly identifiers, and "UUID" to refer to the globally unique identifiers. CualIDs are used by humans when they manually write or enter identifiers, while the longer UUIDs are used by computers to unambiguously reference a sample. Finally, cual-id optionally generates printable label sticker sheets containing Code 128 bar codes and CualIDs for labeling of sample collection and processing materials. IMPORTANCE The adoption of identifiers that are globally unique, correctable, and easily handwritten or manually entered into a computer will be a major step forward for sample tracking in comparative omics studies. As the fields transition to more-centralized sample management, for example, across labs within an institution, across projects funded under a common program, or in systems designed to facilitate meta- and/or integrated analysis, sample identifiers generated with cual-id will not need to change; thus, costly and error-prone updating of data and metadata identifiers will be avoided. Further, using cual-id will ensure that transcription errors in sample identifiers do not require the discarding of otherwise-useful samples that may have been expensive to obtain. Finally, cual-id is simple to install and use and is free for all use. No centralized infrastructure is required to ensure global uniqueness, so it is feasible for any lab to get started using these identifiers within their existing infrastructure.

Geography and Location Are the Primary Drivers of Office Microbiome Composition.

In the United States, humans spend the majority of their time indoors, where they are exposed to the microbiome of the built environment (BE) they inhabit. Despite the ubiquity of microbes in BEs and their potential impacts on health and building materials, basic questions about the microbiology of these environments remain unanswered. We present a study on the impacts of geography, material type, human interaction, location in a room, seasonal variation, and indoor and microenvironmental parameters on bacterial communities in offices. Our data elucidate several important features of microbial communities in BEs. First, under normal office environmental conditions, bacterial communities do not differ on the basis of surface material (e.g., ceiling tile or carpet) but do differ on the basis of the location in a room (e.g., ceiling or floor), two features that are often conflated but that we are able to separate here. We suspect that previous work showing differences in bacterial composition with surface material was likely detecting differences based on different usage patterns. Next, we find that offices have city-specific bacterial communities, such that we can accurately predict which city an office microbiome sample is derived from, but office-specific bacterial communities are less apparent. This differs from previous work, which has suggested office-specific compositions of bacterial communities. We again suspect that the difference from prior work arises from different usage patterns. As has been previously shown, we observe that human skin contributes heavily to the composition of BE surfaces. IMPORTANCE Our study highlights several points that should impact the design of future studies of the microbiology of BEs. First, projects tracking changes in BE bacterial communities should focus sampling efforts on surveying different locations in offices and in different cities but not necessarily different materials or different offices in the same city. Next, disturbance due to repeated sampling, though detectable, is small compared to that due to other variables, opening up a range of longitudinal study designs in the BE. Next, studies requiring more samples than can be sequenced on a single sequencing run (which is increasingly common) must control for run effects by including some of the same samples in all of the sequencing runs as technical replicates. Finally, detailed tracking of indoor and material environment covariates is likely not essential for BE microbiome studies, as the normal range of indoor environmental conditions is likely not large enough to impact bacterial communities.

Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets.

BACKGROUND: Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. MAIN TEXT: We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. CONCLUSIONS: Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are first used with a bioinformatics system. Simplifying the validation of essential tabular data files, such as sample metadata, will reduce common errors and thereby improve the quality and reliability of research outcomes.

Reduced Epithelial Na+/H+ Exchange Drives Gut Microbial Dysbiosis and Promotes Inflammatory Response in T Cell-Mediated Murine Colitis.

Inflammatory bowel diseases (IBD) are associated with functional inhibition of epithelial Na+/H+ exchange. In mice, a selective disruption of NHE3 (Slc9a3), a major apical Na+/H+ exchanger, also promotes IBD-like symptoms and gut microbial dysbiosis. We hypothesized that disruption of Na+/H+ exchange is necessary for the development of dysbiosis, which promotes an exacerbated mucosal inflammatory response. Therefore, we performed a temporal analysis of gut microbiota composition, and mucosal immune response to adoptive T cell transfer was evaluated in Rag2-/- and NHE3-/-/Rag2-/- (DKO) mice with and without broad-spectrum antibiotics. Microbiome (16S profiling), colonic histology, T cell and neutrophil infiltration, mucosal inflammatory tone, and epithelial permeability were analyzed. In adoptive T cell transfer colitis model, Slc9a3 status was the most significant determinant of gut microbial community. In DKO mice, NHE3-deficiency and dysbiosis were associated with dramatically accelerated and exacerbated disease, with rapid body weight loss, increased mucosal T cell and neutrophil influx, increased mucosal cytokine expression, increased permeability, and expansion of CD25-FoxP3+ Tregs; this enhanced susceptibility was alleviated by oral broad-spectrum antibiotics. Based on these results and our previous work, we postulate that epithelial electrolyte homeostasis is an important modulator in the progression of colitis, acting through remodeling of the gut microbial community.

Ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses.

BACKGROUND: Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child. RESULTS: We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes. CONCLUSIONS: The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees. AVAILABILITY: ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .

The Role of Curcumin in Modulating Colonic Microbiota During Colitis and Colon Cancer Prevention.

BACKGROUND: Intestinal microbiota influences the progression of colitis-associated colorectal cancer. With diet being a key determinant of the gut microbial ecology, dietary interventions are an attractive avenue for the prevention of colitis-associated colorectal cancer. Curcumin is the most active constituent of the ground rhizome of the Curcuma longa plant, which has been demonstrated to have anti-inflammatory, antioxidative, and antiproliferative properties. METHODS: Il10 mice on 129/SvEv background were used as a model of colitis-associated colorectal cancer. Starting at 10 weeks of age, wild-type or Il10 mice received 6 weekly intraperitoneal injections of azoxymethane (AOM) or phosphate-buffered saline (PBS) and were started on either a control or a curcumin-supplemented diet. Stools were collected every 4 weeks for microbial community analysis. Mice were killed at 30 weeks of age. RESULTS: Curcumin-supplemented diet increased survival, decreased colon weight/length ratio, and, at 0.5%, entirely eliminated tumor burden. Although colonic histology indicated improvement with curcumin, no effects of mucosal immune responses have been observed in PBS/Il10 mice and limited effects were seen in AOM/Il10 mice. In wild-type and in Il10 mice, curcumin increased bacterial richness, prevented age-related decrease in alpha diversity, increased the relative abundance of Lactobacillales, and decreased Coriobacterales order. Taxonomic profile of AOM/Il10 mice receiving curcumin was more similar to those of wild-type mice than those fed control diet. CONCLUSIONS: In AOM/Il10 model, curcumin reduced or eliminated colonic tumor burden with limited effects on mucosal immune responses. The beneficial effect of curcumin on tumorigenesis was associated with the maintenance of a more diverse colonic microbial ecology.

Regions of homozygosity identified by oligonucleotide SNP arrays: evaluating the incidence and clinical utility.

Copy neutral segments with allelic homozygosity, also known as regions of homozygosity (ROHs), are frequently identified in cases interrogated by oligonucleotide single-nucleotide polymorphism (oligo-SNP) microarrays. Presence of ROHs may be because of parental relatedness, chromosomal recombination or rearrangements and provides important clues regarding ancestral homozygosity, consanguinity or uniparental disomy. In this study of 14 574 consecutive cases, 832 (6%) were found to harbor one or more ROHs over 10 Mb, of which 651 cases (78%) had multiple ROHs, likely because of identity by descent (IBD), and 181 cases (22%) with ROHs involving a single chromosome. Parental relatedness was predicted to be first degree or closer in 5%, second in 9% and third in 19%. Of the 181 cases, 19 had ROHs for a whole chromosome revealing uniparental isodisomy (isoUPD). In all, 25 cases had significant ROHs involving a single chromosome; 5 cases were molecularly confirmed to have a mixed iso- and heteroUPD15 and 1 case each with segmental UPD9pat and segmental UPD22mat; 17 cases were suspected to have a mixed iso- and heteroUPD including 2 cases with small supernumerary marker and 2 cases with mosaic trisomy. For chromosome 15, 12 (92%) of 13 molecularly studied cases had either Prader-Willi or Angelman syndrome. Autosomal recessive disorders were confirmed in seven of nine cases from eight families because of the finding of suspected gene within a ROH. This study demonstrates that ROHs are much more frequent than previously recognized and often reflect parental relatedness, ascertain autosomal recessive diseases or unravel UPD in many cases.

Temporal variability is a personalized feature of the human microbiome.

BACKGROUND: It is now apparent that the complex microbial communities found on and in the human body vary across individuals. What has largely been missing from previous studies is an understanding of how these communities vary over time within individuals. To the extent to which it has been considered, it is often assumed that temporal variability is negligible for healthy adults. Here we address this gap in understanding by profiling the forehead, gut (fecal), palm, and tongue microbial communities in 85 adults, weekly over 3 months. RESULTS: We found that skin (forehead and palm) varied most in the number of taxa present, whereas gut and tongue communities varied more in the relative abundances of taxa. Within each body habitat, there was a wide range of temporal variability across the study population, with some individuals harboring more variable communities than others. The best predictor of these differences in variability across individuals was microbial diversity; individuals with more diverse gut or tongue communities were more stable in composition than individuals with less diverse communities. CONCLUSIONS: Longitudinal sampling of a relatively large number of individuals allowed us to observe high levels of temporal variability in both diversity and community structure in all body habitats studied. These findings suggest that temporal dynamics may need to be considered when attempting to link changes in microbiome structure to changes in health status. Furthermore, our findings show that, not only is the composition of an individual's microbiome highly personalized, but their degree of temporal variability is also a personalized feature.

Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences.

We present a performance-optimized algorithm, subsampled open-reference OTU picking, for assigning marker gene (e.g., 16S rRNA) sequences generated on next-generation sequencing platforms to operational taxonomic units (OTUs) for microbial community analysis. This algorithm provides benefits over de novo OTU picking (clustering can be performed largely in parallel, reducing runtime) and closed-reference OTU picking (all reads are clustered, not only those that match a reference database sequence with high similarity). Because more of our algorithm can be run in parallel relative to "classic" open-reference OTU picking, it makes open-reference OTU picking tractable on massive amplicon sequence data sets (though on smaller data sets, "classic" open-reference OTU clustering is often faster). We illustrate that here by applying it to the first 15,000 samples sequenced for the Earth Microbiome Project (1.3 billion V4 16S rRNA amplicons). To the best of our knowledge, this is the largest OTU picking run ever performed, and we estimate that our new algorithm runs in less than 1/5 the time than would be required of "classic" open reference OTU picking. We show that subsampled open-reference OTU picking yields results that are highly correlated with those generated by "classic" open-reference OTU picking through comparisons on three well-studied datasets. An implementation of this algorithm is provided in the popular QIIME software package, which uses uclust for read clustering. All analyses were performed using QIIME's uclust wrappers, though we provide details (aided by the open-source code in our GitHub repository) that will allow implementation of subsampled open-reference OTU picking independently of QIIME (e.g., in a compiled programming language, where runtimes should be further reduced). Our analyses should generalize to other implementations of these OTU picking algorithms. Finally, we present a comparison of parameter settings in QIIME's OTU picking workflows and make recommendations on settings for these free parameters to optimize runtime without reducing the quality of the results. These optimized parameters can vastly decrease the runtime of uclust-based OTU picking in QIIME.