Applications of species accumulation curves in large-scale biological data analysis

Ex vivo expansion of lung cancer-derived disseminated cancer cells from lymph nodes identifies cells associated with metastatic progression

The cellular basis of the apparent aggressiveness in lung cancer is poorly understood but likely associated with functional or molecular features of disseminated cancer cells (DCCs). DCCs from epithelial cancers are mostly detected by antibodies directed against histogenetic markers such as cytokeratin or EpCAM. It has been argued that marker-negative metastatic founder cells might escape detection. We therefore used ex vivo sphere formation for functional detection of candidate metastasis founders. We generated cell suspensions from 199 LN samples of 131 lung cancer patients and placed them into non-adherent cell culture. Sphere formation was associated with detection of DCCs using EpCAM immunocytology and with significantly poorer prognosis. The prognostic impact of sphere formation was strongly associated with high numbers of EpCAM-positive DCCs and aberrant genotypes of expanded spheres. We also noted sphere formation in patients with no evidence of lymphatic spread, however such spheres showed infrequent expression of signature genes associated with spheres from EpCAM-positive samples and displayed neither typical lung cancer mutations (KRAS, TP53, ERBB1) nor copy number variations, but might be linked to disease progression >5 years post curative surgery. We conclude that EpCAM identifies relevant disease-driving DCCs, that such cells can be expanded for model generation and that further research is needed to clarify the functional and prognostic role of rare EpCAM-negative sphere forming cells.

Alterations and potential roles of microbial population of pregnant mouse saliva and amniotic fluid

PROBLEM

Prenatal exposure to intrauterine inflammation (IUI) is a crucial event in PTB pathophysiology. However, the relationship between microflora and PTB is not fully elucidated.

METHOD OF STUDY

In this study, we established an intrauterine inflammation mouse model via LPS intrauterine injection. The saliva and amniotic fluid were collected for 16s RNA gene sequencing. The levels of TNF-α and IL-1β in mouse amniotic fluid were determined by ELISA assays.

RESULTS

Up to 60% of the operational taxonomic units (OTUs) in the saliva and amniotic fluid of PBS-treated mice were overlapped. LPS treatment-induced changes in the abundance of oral and amniotic fluid microorganisms. Both immune-associated probiotics, salivarius and mastitidis, were still detected in saliva (at significantly increased levels) after LPS-induced intrauterine inflammation and almost no probiotics of any type were detected in amniotic fluid, suggesting that the uterine cavity seems to be more susceptible to LPS compared to the oral cavity. Moreover, the abundance of pathogenic bacteria Escherichia coli was increased in both saliva and amniotic fluid after LPS treatment. The level of TNF-α and IL-1β in amniotic fluid is positively related to the amniotic fluid E. coli abundance.

CONCLUSIONS

The microbial composition of saliva and amniotic fluid of pregnant mice was similar. LPS-induced intrauterine inflammation decreased the consistency of microbial composition in mouse saliva and amniotic fluid, increased the abundance of E. coli in saliva and amniotic fluid, and decreased the abundance of immune-associated probiotics, especially in amniotic fluid.

DNA barcodes provide insights into the diversity and biogeography of the non-biting midge Polypedilum (Diptera, Chironomidae) in South America

South America, particularly within its tropical belt, is renowned for its unparalleled high levels of species richness, surpassing other major biomes. Certain neotropical areas harbor fragmented knowledge of insect diversity and face imminent threats from biodiversity loss and climate change. Hence, there is an urgent need for rapid estimation methods to complement slower traditional taxonomic approaches. A variety of algorithms for delimiting species through single-locus DNA barcodes have been developed and applied for rapid species diversity estimates across diverse taxa. However, tree-based and distance-based methods may yield different group assignments, leading to potential overestimation or underestimation of putative species. Here, we investigate the performance of different DNA-based species delimitation approaches to rapidly estimate the diversity of Polypedilum (Chironomidae, Diptera) in South America. Additionally, we test the hypothesis that significant differences exist in the community structure of Polypedilum fauna between South America and its neighboring regions, particularly the Nearctic. Our analysis encompasses a dataset of 1492 specimens from 598 locations worldwide, with a specific focus on South America. Within this region, we analyzed a subset of 247 specimens reported from 37 locations. Using various methods including the Barcode Index Number (BIN), Bayesian Poisson tree processes (bPTP), multi-rate Poisson tree processes (mPTP), single-rate Poisson tree processes (sPTP), and generalized mixed Yule coalescent (sGMYC), we identify molecular operational taxonomic units (MOTUs) ranging from 267 to 520. Our results indicate that the sGMYC method is the most suitable for estimating putative species in our dataset, resulting in the identification of 75 species in the Neotropical region, particularly in South America. Notably, this region exhibited higher species richness in comparison to the Palearctic and Oriental realms. Additionally, our findings suggest potential differences in species composition of Polypedilum fauna between the Neotropical and the adjacent Nearctic realms, highlighting high levels of endemism and species richness in the first. These results support our hypothesis that there are substantial differences exist in species composition between the Polypedilum fauna in South America and the neighboring regions.

Woody species diversity and regeneration status of Sub-Alpine forest of Mount Adama exclosure site, Northwestern highlands of Ethiopia

Forests provide a wide range of ecosystem services. Despite these facts, the expansion of agriculture and settlement at the expense of forest resources has threatened the forest resources and results in biodiversity loss. To halt this problem, various conservation practices that believed to restore the degraded lands and biodiversity of the country have been implemented. Area exclosure is among the conservation strategies that have been used to restore the degraded lands in Mount Adama forest. However, its role in woody species regeneration in Mount Adama was not investigated. Thus, the objective of the study was to evaluate the impact of area exclosure on woody plant species composition, regeneration status, structure and diversity in Mount Adama. A systematic transect sampling method was used to collect vegetation data. Hence, 53 plots with 400 m² area were laid along 11 transects. Then, within the main plots, five subplots with 1 m² were laid to determine the abundance and frequency of seedlings. The results showed that about 31 woody species that belong to 30 genera and 19 families including four endemic species were identified. The majority (67.74%) of the species were categorized under shrub habitat, while the remaining 19.35% and 12.90% were trees and lianas or climbers, respectively. Asteraceae family was dominant by contributing 4 species followed by Rosaceae and Solanaceae each contributed 3 species. Hypericum revolutum was the dominant species with 53.38 important value index followed by Erica arborea and Hagenia abyssinica with 49.12 and 40.05, respectively. The overall Shannon- Wiener diversity index and Shannon evenness in the exclosure site were 2.6 and 0.73, respectively. Furthermore, the number of seedlings and saplings were higher in the exclosure than the untreated site. The results of the study evidently showed that area exclosure that implemented in Mount Adam successfully contributed to the biodiversity restoration. Therefore, further conservation efforts targeting species with low IVI values are needed for sustainable management and ecological recovery of the area.

Victim identification from the September 11, 2001 attack on the World Trade Center: Past trends and future projections

Victim identification following mass fatality events is critically important. Extensive traumatic injuries and body fragmentation add complexity to this process. World Trade Center (WTC) identification efforts have been ongoing for over 20 years and this study tracks identification trends from the 2753 known WTC victims and the 21,905 recovered remains. For identified victims, data include the number of remains identified, date(s) of the identification(s), and identification modalities. Results show a heavy reliance on DNA due to body fragmentation. Other modalities played an important role initially, but DNA eventually became the singular identification modality. For large-scale disasters involving significant body fragmentation, aggressive DNA testing strategies are critical for victim identification. Over time, the number of linked remains (portions of previously identified individuals) will greatly outnumber the new identifications (first-time identifications). A novel approach using statistical modeling from ecology studies was applied to estimate future WTC identification rates using Identification Accumulation Curve extrapolation with the Good-Toulmin estimator. Projections indicate there will be 76 first-time identifications (95% CI: 49-117) through the successful DNA testing of 3404 unidentified, fragmentary remains. The remainder of the identifications would be additional portions of previously identified victims. These results may be instructional for management of other large-scale, protracted victim identification efforts.

Analysis of human brain tissue derived from DBS surgery

Background

Transcriptomic and proteomic profiling of human brain tissue is hindered by the availability of fresh samples from living patients. Postmortem samples usually represent the advanced disease stage of the patient. Furthermore, the postmortem interval can affect the transcriptomic and proteomic profiles. Therefore, fresh brain tissue samples from living patients represent a valuable resource of metabolically intact tissue. Implantation of deep brain stimulation (DBS) electrodes into the human brain is a neurosurgical treatment for, e.g., movement disorders. Here, we describe an improved approach to collecting brain tissues from surgical instruments used in implantation of DBS device for transcriptomics and proteomics analyses.

Methods

Samples were extracted from guide tubes and recording electrodes used in routine DBS implantation procedure to treat patients with Parkinson’s disease, genetic dystonia and tremor. RNA sequencing was performed in tissues extracted from the recording microelectrodes and liquid chromatography-mass spectrometry (LC-MS) performed in tissues from guide tubes. To assess the performance of the current approach, the obtained datasets were compared with previously published datasets representing brain tissues.

Results

Altogether, 32,034 RNA transcripts representing the unique Ensembl gene identifiers were detected from eight samples representing both hemispheres of four patients. By using  LC-MS, we identified 734 unique proteins from 31 samples collected from 14 patients. The datasets are available in the BioStudies database (accession number S-BSST667). Our results indicate that surgical instruments used in DBS installation retain brain material sufficient for protein and gene expression studies. Comparison with previously published datasets obtained with similar approach proved the robustness and reproducibility of the protocol.

Conclusions

The instruments used during routine DBS surgery are a useful source for obtaining fresh brain tissues from living patients. This approach overcomes the issues that arise from using postmortem tissues, such as the effect of postmortem interval on transcriptomic and proteomic landscape of the brain, and can be used for studying molecular aspects of DBS-treatable diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40035-022-00297-y.

Cellular abundance shapes function in piRNA-guided genome defense

Defense against genome invaders universally relies on RNA-guided immunity. Prokaryotic CRISPR-Cas and eukaryotic RNA interference pathways recognize targets by complementary base-pairing, which places the sequences of their guide RNAs at the center of self/nonself discrimination. Here, we explore the sequence space of PIWI-interacting RNAs (piRNAs), the genome defense of animals, and establish functional priority among individual sequences. Our results reveal that only the topmost abundant piRNAs are commonly present in every cell, whereas rare sequences generate cell-to-cell diversity in flies and mice. We identify a skewed distribution of sequence abundance as a hallmark of piRNA populations and show that quantitative differences of more than a 1000-fold are established by conserved mechanisms of biogenesis. Finally, our genomics analyses and direct reporter assays reveal that abundance determines function in piRNA-guided genome defense. Taken together, we identify an effective sequence space and untangle two classes of piRNAs that differ in complexity and function. The first class represents the topmost abundant sequences and drives silencing of genomic parasites. The second class sparsely covers an enormous sequence space. These rare piRNAs cannot function in every cell, every individual, or every generation but create diversity with potential for adaptation in the ongoing arms race with genome invaders.

Urban Aerobiomes are Influenced by Season, Vegetation, and Individual Site Characteristics

Exposure to biodiverse environments such as forests can benefit human well-being, and evidence suggests exposure to high microbial diversity may improve mental and immune health. However, the factors that drive microbial community assembly are poorly understood, as is the relationship between exposure to these communities and human health. We characterized airborne bacterial communities in two disparate types of urban greenspace (forest and grass) in late-spring 2017 at sites previously sampled in late-summer 2015 in Eugene-Springfield, Oregon, using high-throughput metabarcode sequencing. While all sites shared a core aerobiome in late-spring consisting of plant- and soil-associated genera, forests had significantly higher diversity than grass sites (F = 12, P = 0.004). Vegetation type explained 14% of the difference between forest and grass aerobiomes, yet individual site location explained 41% of the variation. These results were similar to but amplified over those from late summer, suggesting that both aerobiome diversity and vegetation-driven effects are higher when deciduous foliage is fresher and more active, temperatures cooler, and humidity higher. Continued exploration and hypothesis-driven research will enable development of mechanistic theory describing key drivers of urban aerobiome assembly and its relationship to human health, which, in turn, will help urban designers and planners create evidence-based salutogenic cities for future generations.

BUTTERFLY: addressing the pooled amplification paradox with unique molecular identifiers in single-cell RNA-seq

The incorporation of unique molecular identifiers (UMIs) in single-cell RNA-seq assays makes possible the identification of duplicated molecules, thereby facilitating the counting of distinct molecules from sequenced reads. However, we show that the naïve removal of duplicates can lead to a bias due to a "pooled amplification paradox," and we propose an improved quantification method based on unseen species modeling. Our correction called BUTTERFLY uses a zero truncated negative binomial estimator implemented in the kallisto bustools workflow. We demonstrate its efficacy across cell types and genes and show that in some cases it can invert the relative abundance of genes.

Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq

Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: integrated cellular indexing of chromatin landscape and epitopes, called ICICLE-seq. We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures transcriptomics (scRNA-seq), epitopes, and chromatin accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

Mithramycin induces promoter reprogramming and differentiation of rhabdoid tumor

Rhabdoid tumor (RT) is a pediatric cancer characterized by the inactivation of SMARCB1, a subunit of the SWI/SNF chromatin remodeling complex. Although this deletion is the known oncogenic driver, there are limited effective therapeutic options for these patients. Here we use unbiased screening of cell line panels to identify a heightened sensitivity of rhabdoid tumor to mithramycin and the second-generation analogue EC8042. The sensitivity of MMA and EC8042 was superior to traditional DNA damaging agents and linked to the causative mutation of the tumor, SMARCB1 deletion. Mithramycin blocks SMARCB1-deficient SWI/SNF activity and displaces the complex from chromatin to cause an increase in H3K27me3. This triggers chromatin remodeling and enrichment of H3K27ac at chromHMM-defined promoters to restore cellular differentiation. These effects occurred at concentrations not associated with DNA damage and were not due to global chromatin remodeling or widespread gene expression changes. Importantly, a single 3-day infusion of EC8042 caused dramatic regressions of RT xenografts, recapitulated the increase in H3K27me3, and cellular differentiation described in vitro to completely cure three out of eight mice.

Online searching platform for the antibiotic resistome in bacterial tree of life and global habitats

Metagenomic analysis reveals that antibiotic-resistance genes (ARGs) are widely distributed in both human-associated and non-human-associated habitats. However, it is difficult to equally compare ARGs between samples without a standard method. Here, we constructed a comprehensive profile of the distribution of potential ARGs in bacterial tree of life and global habitats by investigating ARGs in 55 000 bacterial genomes, 16 000 bacterial plasmid sequences, 3000 bacterial integron sequences and 850 metagenomes using a standard pipeline. We found that >80% of all known ARGs are not carried by any plasmid or integron sequences. Among potential mobile ARGs, tetracycline and beta-lactam resistance genes (such as tetA, tetM and class A beta-lactamase gene) distribute in multiple pathogens across bacterial phyla, indicating their clinical relevance and importance. We showed that class 1 integrases (intI1) display a poor linear relationship with total ARGs in both non-human-associated and human-associated environments. Furthermore, both total ARGs and intI1 genes show little correlation with the degree of anthropogenicity. These observations highlight the need to differentiate ARGs of high clinical relevance. This profile is published on an online platform (ARGs-OSP, http://args-osp.herokuapp.com/) as a valuable resource for the most challenging topics in this field, i.e. the risk, evolution and emergence of ARGs.

A Highly Scalable Method for Joint Whole-Genome Sequencing and Gene-Expression Profiling of Single Cells

To address how genetic variation alters gene expression in complex cell mixtures, we developed direct nuclear tagmentation and RNA sequencing (DNTR-seq), which enables whole-genome and mRNA sequencing jointly in single cells. DNTR-seq readily identified minor subclones within leukemia patients. In a large-scale DNA damage screen, DNTR-seq was used to detect regions under purifying selection and identified genes where mRNA abundance was resistant to copy-number alteration, suggesting strong genetic compensation. mRNA sequencing (mRNA-seq) quality equals RNA-only methods, and the low positional bias of genomic libraries allowed detection of sub-megabase aberrations at ultra-low coverage. Each cell library is individually addressable and can be re-sequenced at increased depth, allowing multi-tiered study designs. Additionally, the direct tagmentation protocol enables coverage-independent estimation of ploidy, which can be used to identify cell singlets. Thus, DNTR-seq directly links each cell's state to its corresponding genome at scale, enabling routine analysis of heterogeneous tumors and other complex tissues.

The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack

We describe the evolution of a stereotype as it emerged in tweets about the Charlie Hebdo terrorist attack in Paris in early 2015. Our focus is on terms associated with the Muslim community and the Islamic world. The data (400k tweets) were collected via Twitter streaming API and consisted of tweets that contained at least one of 16 hashtags associated with the Charlie Hebdo attack (e.g., #JeSuisCharlie, #IAmCharlie, #ParisAttacks), collected between January 14th and February 9th. From these data, we generated pairwise co-occurrence frequencies between key words such as “Islam”, “Muslim(s)”, “Arab(s)”, and “The Prophet” and possible associates such as: “terrorism”, “terror”, “terrorist(s)”, “kill(ed)”, “free”, “freedom” and “love”. We use changes in frequency of co-occurring words to define ways in which acute negative and positive stereotypes towards Muslims and Islam arise and evolve in three phases during the period of interest. We identify a positively-valenced backlash in a subset of tweets associated with the “origins of Islam”. Results depict the emergence and transformation of implicit online stereotypes related to Islam from naturally occurring social media data and how pro-as well as anti-Islam online small-world networks evolve in response to a terrorist attack.

Recent increases in assemblage rarity are linked to increasing local immigration

As pressures on biodiversity increase, a better understanding of how assemblages are responding is needed. Because rare species, defined here as those that have locally low abundances, make up a high proportion of assemblage species lists, understanding how the number of rare species within assemblages is changing will help elucidate patterns of recent biodiversity change. Here, we show that the number of rare species within assemblages is increasing, on average, across systems. This increase could arise in two ways: species already present in the assemblage decreasing in abundance but with no increase in extinctions, or additional species entering the assemblage in low numbers associated with an increase in immigration. The positive relationship between change in rarity and change in species richness provides evidence for the second explanation, i.e. higher net immigration than extinction among the rare species. These measurable changes in the structure of assemblages in the recent past underline the need to use multiple biodiversity metrics to understand biodiversity change.

Deciphering eukaryotic gene-regulatory logic with 100 million random promoters

How transcription factors (TFs) interpret cis-regulatory DNA sequence to control gene expression remains unclear, largely because past studies using native and engineered sequences had insufficient scale. Here, we measure the expression output of >100 million synthetic yeast promoter sequences that are fully random. These sequences yield diverse, reproducible expression levels that can be explained by their chance inclusion of functional TF binding sites. We use machine learning to build interpretable models of transcriptional regulation that predict ~94% of the expression driven from independent test promoters and ~89% of the expression driven from native yeast promoter fragments. These models allow us to characterize each TF’s specificity, activity, and interactions with chromatin. TF activity depends on binding-site strand, position, DNA helical face and chromatin context. Notably, expression level is influenced by weak regulatory interactions, which confound designed-sequence studies. Our analyses show that massive-throughput assays of fully random DNA can provide the big data necessary to develop complex, predictive models of gene regulation.

Gene expression levels in yeast are predicted using a massive dataset on promoters with random sequences.

Opportunities for improving cancer treatment using systems biology

Current cancer therapies target a limited set of tumor features, rather than considering the tumor as a whole. Systems biology aims to reveal therapeutic targets associated with a variety of facets in an individual's tumor, such as genetic heterogeneity and its evolution, cancer cell-autonomous phenotypes, and microenvironmental signaling. These disparate characteristics can be reconciled using mathematical modeling that incorporates concepts from ecology and evolution. This provides an opportunity to predict tumor growth and response to therapy, to tailor patient-specific approaches in real time or even prospectively. Importantly, as data regarding patient tumors is often available from only limited time points during treatment, systems-based approaches can address this limitation by interpolating longitudinal events within a principled framework. This review outlines areas in medicine that could benefit from systems biology approaches to deconvolve the complexity of cancer.

Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments

For many types of high-throughput sequencing experiments, success in downstream analysis depends on attaining sufficient coverage for individual positions in the genome. For example, when identifying single-nucleotide variants de novo, the number of reads supporting a particular variant call determines our confidence in that variant call. If sequenced reads are distributed uniformly along the genome, the coverage of a nucleotide position is easily approximated by a Poisson distribution, with rate equal to average sequencing depth. Unfortunately, as has become well known, high-throughput sequencing data are never uniform. The numerous factors contributing to variation in coverage have resisted attempts at direct modeling and change along with minor adjustments in the underlying technology. We propose a new nonparametric method to predict the portion of a genome that will attain some specified minimum coverage, as a function of sequencing effort, using information from a shallow sequencing experiment from the same library. Simulations show our approach performs well under an array of distributional assumptions that deviate from uniformity. We applied this approach to estimate coverage at varying depths in single-cell whole-genome sequencing data from multiple protocols. These resulted in highly accurate predictions, demonstrating the effectiveness of our approach in analyzing complexity of sequencing libraries and optimizing design of sequencing experiments.

Nasal Vaccination Drives Modifications of Nasal and Systemic Antibody Repertoires in Rainbow Trout

Bony fish represent the most basal vertebrate branch with a dedicated mucosal immune system, which comprises immunologically heterogeneous microenvironments armed with innate and adaptive components. In rainbow trout (Oncorhynchus mykiss), a nasopharynx-associated lymphoid tissue (NALT) was recently described as a diffuse network of myeloid and lymphoid cells located in the olfactory organ of fish. Several studies have demonstrated high levels of protection conferred by nasal vaccines against viral and bacterial pathogens; however, the mechanisms underlying the observed protection are not well understood. We applied 5'RACE and a deep sequencing-based approach to investigate the clonal structure of the systemic and mucosal rainbow trout B cell repertoire. The analysis of Ig repertoire in control trout suggests different structures of IgM and IgT spleen and NALT repertoires, with restricted repertoire diversity in NALT. Nasal and injection vaccination with a bacterial vaccine revealed unique dynamics of IgM and IgT repertoires at systemic and mucosal sites and the remarkable ability of nasal vaccines to induce spleen Ig responses. Our findings provide an important immunological basis for the effectiveness of nasal vaccination in fish and other vertebrate animals and will help the design of future nasal vaccination strategies.

Molecular Heterogeneity in Large-Scale Biological Data: Techniques and Applications

High-throughput sequencing technologies have evolved at a stellar pace for almost a decade and have greatly advanced our understanding of genome biology. In these sampling-based technologies, there is an important detail that is often overlooked in the analysis of the data and the design of the experiments, specifically that the sampled observations often do not give a representative picture of the underlying population. This has long been recognized as a problem in statistical ecology and in the broader statistics literature. In this review, we discuss the connections between these fields, methodological advances that parallel both the needs and opportunities of large-scale data analysis, and specific applications in modern biology. In the process we describe unique aspects of applying these approaches to sequencing technologies, including sequencing error, population and individual heterogeneity, and the design of experiments.

MMP-9 inhibition promotes anti-tumor immunity through disruption of biochemical and physical barriers to T-cell trafficking to tumors

Matrix metalloproteinase-9 (MMP-9), whose expression is frequently dysregulated in cancer, promotes tumor growth, invasion, and metastasis by multiple mechanisms, including extracellular matrix remodeling and growth-factor and cytokine activation. We developed a monoclonal antibody against murine MMP-9, which we found decreased growth of established primary tumors in an orthotopic model of HER2-driven breast cancer (HC11-NeuT) in immunocompetent mice. RNA sequencing (RNAseq) profiling of NeuT tumors and additional mouse model tumors revealed that anti-MMP-9 treatment resulted in upregulation of immune signature pathways associated with cytotoxic T-cell response. As there is a need to boost the low response rates observed with anti-PDL1 antibody treatment in the clinical setting, we assessed the potential of anti-MMP-9 to improve T-cell response to immune checkpoint inhibitor anti-PDL1 in NeuT tumors. Anti-MMP-9 and anti-PDL1 cotreatment reduced T-cell receptor (TCR) clonality and increased TCR diversity, as detected by TCR sequencing of NeuT tumors. Flow cytometry analyses of tumors showed that the combination treatment increased the frequency of CD3+ T cells, including memory/effector CD4 and CD8 T cells, but not regulatory T cells, among tumor-infiltrating leukocytes. Moreover, in vitro enzymatic assays corroborated that MMP-9 cleaves key T-cell chemoattractant CXC receptor 3 ligands (CXC ligand [CXCL] 9, CXCL10, and CXCL11) and renders them inactive in T-cell migration assays. Consistent with our in vitro experiments, analysis of NeuT tumor protein lysates showed that anti-MMP-9 treatment increases expression of CXCL10 and other T cell–stimulating factors, such as interleukin (IL)-12p70 and IL-18. We show that inhibition of MMP-9, a key component of the tumor-promoting and immune-suppressive myeloid inflammatory milieu, increases T-helper cell 1 type cytokines, trafficking of effector/memory T cells into tumors, and intratumoral T-cell diversity.

In-solution Y-chromosome capture-enrichment on ancient DNA libraries

Background

As most ancient biological samples have low levels of endogenous DNA, it is advantageous to enrich for specific genomic regions prior to sequencing. One approach—in-solution capture-enrichment—retrieves sequences of interest and reduces the fraction of microbial DNA. In this work, we implement a capture-enrichment approach targeting informative regions of the Y chromosome in six human archaeological remains excavated in the Caribbean and dated between 200 and 3000 years BP. We compare the recovery rate of Y-chromosome capture (YCC) alone, whole-genome capture followed by YCC (WGC + YCC) versus non-enriched (pre-capture) libraries.

Results

The six samples show different levels of initial endogenous content, with very low (< 0.05%, 4 samples) or low (0.1–1.54%, 2 samples) percentages of sequenced reads mapping to the human genome. We recover 12–9549 times more targeted unique Y-chromosome sequences after capture, where 0.0–6.2% (WGC + YCC) and 0.0–23.5% (YCC) of the sequence reads were on-target, compared to 0.0–0.00003% pre-capture. In samples with endogenous DNA content greater than 0.1%, we found that WGC followed by YCC (WGC + YCC) yields lower enrichment due to the loss of complexity in consecutive capture experiments, whereas in samples with lower endogenous content, the libraries’ initial low complexity leads to minor proportions of Y-chromosome reads. Finally, increasing recovery of informative sites enabled us to assign Y-chromosome haplogroups to some of the archeological remains and gain insights about their paternal lineages and origins.

Conclusions

We present to our knowledge the first in-solution capture-enrichment method targeting the human Y-chromosome in aDNA sequencing libraries. YCC and WGC + YCC enrichments lead to an increase in the amount of Y-DNA sequences, as compared to libraries not enriched for the Y-chromosome. Our probe design effectively recovers regions of the Y-chromosome bearing phylogenetically informative sites, allowing us to identify paternal lineages with less sequencing than needed for pre-capture libraries. Finally, we recommend considering the endogenous content in the experimental design and avoiding consecutive rounds of capture, as clonality increases considerably with each round.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4945-x) contains supplementary material, which is available to authorized users.

Unbiased quantification of immunoglobulin diversity at the DNA level with VDJ-seq

For high-throughput sequencing and quantification of immunoglobulin repertoires, most methodologies use RNA. However, output varies enormously between recombined genes due to different promoter strengths and differential activation of lymphocyte subsets, precluding quantitation of recombinants on a per-cell basis. To date, DNA-based approaches have used V gene primer cocktails, with substantial inherent biases. Here, we describe VDJ sequencing (VDJ-seq), which accurately quantitates immunoglobulin diversity at the DNA level in an unbiased manner. This is accomplished with a single primer-extension step using biotinylated J gene primers. By addition of unique molecular identifiers (UMIs) before primer extension, we reliably remove duplicate sequences and correct for sequencing and PCR errors. Furthermore, VDJ-seq captures productive and nonproductive VDJ and DJ recombination events on a per-cell basis. Library preparation takes 3 d, with 2 d of sequencing and 1 d of data processing and analysis.

A novel method to determine the minimum number of sequences required for reliable microbial community analysis

Although high-throughput sequencing is an efficient approach to study the structure of microbial communities in detail, it is still impossible to enumerate all individuals using this method. Therefore, it is a common strategy to generate sampling datasets that are representative of the assemblages. However, the representativeness of these sampling datasets has never been assessed. In this study, we developed a method to determine the minimum number sequences that are required to be analyzed to obtain a reliable description of microbial community structure. First, a set of datasets from microbial communities were constructed by in silico sampling at different depths. Second, the correlation equation between dissimilarity of the sampling datasets and sampling depths was fitted, and thereby the minimum number of 16S rRNA gene sequences was predicted. Finally, we verified the method using empirical data of microbiota from a laboratory mesocosm. Our method showed that at least 5,528,079 sequences were required to reliably characterize microbial communities inhabiting the mesocosms. However, if only dominant OTUs (>1%) were considered, thousands of sequences were enough. This promising method provides a criterion to ensure sequencing sufficiency when analyzing the structure of natural microbial communities.

Design, execution, and analysis of pooled in vitro CRISPR/Cas9 screens

The recently described clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology has proven to be an exquisitely powerful and invaluable method of genetic manipulation and/or modification. As such, many researchers have realized the potential of using the CRISPR/Cas9 system as a novel screening method for the identification of important proteins in biological processes and have designed short guide RNA libraries for an in vitro screening. The seminal papers describing these libraries offer valuable information regarding methods for generating the short guide RNA libraries, creating cell lines containing these libraries, and specific details regarding the screening workflow. However, certain considerations are often overlooked that may be important when planning and performing a screen, including which CRISPR library to use and how to best analyze the resulting screen data. In this review, we offer suggestions to answer some of these questions that are not covered as deeply in the papers describing the available CRISPR libraries for an in vitro screening.