High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing.

Understanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single-neuron resolution and high throughput, a challenging combination with conventional methods. Here, we introduce barcoded anatomy resolved by sequencing (BARseq), a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3,579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (intratelencephalic [IT], pyramidal tract-like [PT-like], and corticothalamic [CT]) of projection neurons. In depth analysis uncovered a projection type restricted almost exclusively to transcriptionally defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.

IL-1R3 blockade broadly attenuates the functions of six members of the IL-1 family, revealing their contribution to models of disease.

Interleukin (IL)-1R3 is the co-receptor in three signaling pathways that involve six cytokines of the IL-1 family (IL-1α, IL-1ß, IL-33, IL-36α, IL-36ß and IL-36γ). In many diseases, multiple cytokines contribute to disease pathogenesis. For example, in asthma, both IL-33 and IL-1 are of major importance, as are IL-36 and IL-1 in psoriasis. We developed a blocking monoclonal antibody (mAb) to human IL-1R3 (MAB-hR3) and demonstrate here that this antibody specifically inhibits signaling via IL-1, IL-33 and IL-36 in vitro. Also, in three distinct in vivo models of disease (crystal-induced peritonitis, allergic airway inflammation and psoriasis), we found that targeting IL-1R3 with a single mAb to mouse IL-1R3 (MAB-mR3) significantly attenuated heterogeneous cytokine-driven inflammation and disease severity. We conclude that in diseases driven by multiple cytokines, a single antagonistic agent such as a mAb to IL-1R3 is a therapeutic option with considerable translational benefit.

Whole-cortex in situ sequencing reveals input-dependent area identity.

The cerebral cortex is composed of neuronal types with diverse gene expression that are organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture1,2, connectivity3,4 and neuronal activity5,6, are wired into modular networks3,4,7. However, it remains unclear whether these spatial organizations are reflected in neuronal transcriptomic signatures and how such signatures are established in development. Here we used BARseq, a high-throughput in situ sequencing technique, to interrogate the expression of 104 cell-type marker genes in 10.3 million cells, including 4,194,658 cortical neurons over nine mouse forebrain hemispheres, at cellular resolution. De novo clustering of gene expression in single neurons revealed transcriptomic types consistent with previous single-cell RNA sequencing studies8,9. The composition of transcriptomic types is highly predictive of cortical area identity. Moreover, areas with similar compositions of transcriptomic types, which we defined as cortical modules, overlap with areas that are highly connected, suggesting that the same modular organization is reflected in both transcriptomic signatures and connectivity. To explore how the transcriptomic profiles of cortical neurons depend on development, we assessed cell-type distributions after neonatal binocular enucleation. Notably, binocular enucleation caused the shifting of the cell-type compositional profiles of visual areas towards neighbouring cortical areas within the same module, suggesting that peripheral inputs sharpen the distinct transcriptomic identities of areas within cortical modules. Enabled by the high throughput, low cost and reproducibility of BARseq, our study provides a proof of principle for the use of large-scale in situ sequencing to both reveal brain-wide molecular architecture and understand its development.

Comparative cellular analysis of motor cortex in human, marmoset and mouse.

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

Cellular anatomy of the mouse primary motor cortex.

An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input-output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture.

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes.

MOTIVATION: Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. RESULTS: In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.

Improving replicability in single-cell RNA-Seq cell type discovery with Dune.

BACKGROUND: Single-cell transcriptome sequencing (scRNA-Seq) has allowed new types of investigations at unprecedented levels of resolution. Among the primary goals of scRNA-Seq is the classification of cells into distinct types. Many approaches build on existing clustering literature to develop tools specific to single-cell. However, almost all of these methods rely on heuristics or user-supplied parameters to control the number of clusters. This affects both the resolution of the clusters within the original dataset as well as their replicability across datasets. While many recommendations exist, in general, there is little assurance that any given set of parameters will represent an optimal choice in the trade-off between cluster resolution and replicability. For instance, another set of parameters may result in more clusters that are also more replicable. RESULTS: Here, we propose Dune, a new method for optimizing the trade-off between the resolution of the clusters and their replicability. Our method takes as input a set of clustering results-or partitions-on a single dataset and iteratively merges clusters within each partitions in order to maximize their concordance between partitions. As demonstrated on multiple datasets from different platforms, Dune outperforms existing techniques, that rely on hierarchical merging for reducing the number of clusters, in terms of replicability of the resultant merged clusters as well as concordance with ground truth. Dune is available as an R package on Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/Dune.html . CONCLUSIONS: Cluster refinement by Dune helps improve the robustness of any clustering analysis and reduces the reliance on tuning parameters. This method provides an objective approach for borrowing information across multiple clusterings to generate replicable clusters most likely to represent common biological features across multiple datasets.

Assessing the replicability of spatial gene expression using atlas data from the adult mouse brain.

High-throughput, spatially resolved gene expression techniques are poised to be transformative across biology by overcoming a central limitation in single-cell biology: the lack of information on relationships that organize the cells into the functional groupings characteristic of tissues in complex multicellular organisms. Spatial expression is particularly interesting in the mammalian brain, which has a highly defined structure, strong spatial constraint in its organization, and detailed multimodal phenotypes for cells and ensembles of cells that can be linked to mesoscale properties such as projection patterns, and from there, to circuits generating behavior. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain subdivisions, between the Allen Institute's in situ hybridization data from the adult mouse brain (Allen Brain Atlas (ABA)) and a similar dataset collected using spatial transcriptomics (ST). With the advent of tractable spatial techniques, for the first time, we are able to benchmark the Allen Institute's whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. We use regularized linear regression (LASSO), linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen Reference Atlas labels are classifiable using transcription in both data sets, but that performance is higher in the ABA than in ST. Furthermore, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bidirectionally. While an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. In general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability ultimately providing a valuable reference set for understanding the cell biology of the brain.

Cell targeting and immunostimulatory properties of a novel Fcγ-receptor-independent agonistic anti-CD40 antibody in rhesus macaques.

Targeting CD40 by agonistic antibodies used as vaccine adjuvants or for cancer immunotherapy is a strategy to stimulate immune responses. The majority of studied agonistic anti-human CD40 antibodies require crosslinking of their Fc region to inhibitory FcγRIIb to induce immune stimulation although this has been associated with toxicity in previous studies. Here we introduce an agonistic anti-human CD40 monoclonal IgG1 antibody (MAB273) unique in its specificity to the CD40L binding site of CD40 but devoid of Fcγ-receptor binding. We demonstrate rapid binding of MAB273 to B cells and dendritic cells resulting in activation in vitro on human cells and in vivo in rhesus macaques. Dissemination of fluorescently labeled MAB273 after subcutaneous administration was found predominantly at the site of injection and specific draining lymph nodes. Phenotypic cell differentiation and upregulation of genes associated with immune activation were found in the targeted tissues. Antigen-specific T cell responses were enhanced by MAB273 when given in a prime-boost regimen and for boosting low preexisting responses. MAB273 may therefore be a promising immunostimulatory adjuvant that warrants future testing for therapeutic and prophylactic vaccination strategies.

Copolymerization of single-cell nucleic acids into balls of acrylamide gel.

We show the use of 5'-Acrydite oligonucleotides to copolymerize single-cell DNA or RNA into balls of acrylamide gel (BAGs). Combining this step with split-and-pool techniques for creating barcodes yields a method with advantages in cost and scalability, depth of coverage, ease of operation, minimal cross-contamination, and efficient use of samples. We perform DNA copy number profiling on mixtures of cell lines, nuclei from frozen prostate tumors, and biopsy washes. As applied to RNA, the method has high capture efficiency of transcripts and sufficient consistency to clearly distinguish the expression patterns of cell lines and individual nuclei from neurons dissected from the mouse brain. By using varietal tags (UMIs) to achieve sequence error correction, we show extremely low levels of cross-contamination by tracking source-specific SNVs. The method is readily modifiable, and we will discuss its adaptability and diverse applications.

Defining the extent of gene function using ROC curvature.

MOTIVATION: Interactions between proteins help us understand how genes are functionally related and how they contribute to phenotypes. Experiments provide imperfect 'ground truth' information about a small subset of potential interactions in a specific biological context, which can then be extended to the whole genome across different contexts, such as conditions, tissues or species, through machine learning methods. However, evaluating the performance of these methods remains a critical challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves. RESULTS: We identify Functional Equivalence Classes (FECs), subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves built from gene-centric prediction tasks, such as function or interaction predictions. FECs are widespread across data types and methods, they can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10-50 genes), and tissue-specific secondary markers (100-500 genes). In addition, FECs suggest the existence of functional modules that span a wide range of the genome, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in the definition of functional gene sets. AVAILABILITY AND IMPLEMENTATION: Code for analyses and figures is available at https://github.com/yexilein/pyroc. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A novel anti-human IL-1R7 antibody reduces IL-18-mediated inflammatory signaling.

Unchecked inflammation can result in severe diseases with high mortality, such as macrophage activation syndrome (MAS). MAS and associated cytokine storms have been observed in COVID-19 patients exhibiting systemic hyperinflammation. Interleukin-18 (IL-18), a proinflammatory cytokine belonging to the IL-1 family, is elevated in both MAS and COVID-19 patients, and its level is known to correlate with the severity of COVID-19 symptoms. IL-18 binds its specific receptor IL-1 receptor 5 (IL-1R5, also known as IL-18 receptor alpha chain), leading to the recruitment of the coreceptor, IL-1 receptor 7 (IL-1R7, also known as IL-18 receptor beta chain). This heterotrimeric complex then initiates downstream signaling, resulting in systemic and local inflammation. Here, we developed a novel humanized monoclonal anti-IL-1R7 antibody to specifically block the activity of IL-18 and its inflammatory signaling. We characterized the function of this antibody in human cell lines, in freshly obtained peripheral blood mononuclear cells (PBMCs) and in human whole blood cultures. We found that the anti-IL-1R7 antibody significantly suppressed IL-18-mediated NFκB activation, reduced IL-18-stimulated IFNγ and IL-6 production in human cell lines, and reduced IL-18-induced IFNγ, IL-6, and TNFα production in PBMCs. Moreover, the anti-IL-1R7 antibody significantly inhibited LPS- and Candida albicans-induced IFNγ production in PBMCs, as well as LPS-induced IFNγ production in whole blood cultures. Our data suggest that blocking IL-1R7 could represent a potential therapeutic strategy to specifically modulate IL-18 signaling and may warrant further investigation into its clinical potential for treating IL-18-mediated diseases, including MAS and COVID-19.

Nanodiamond Theranostic for Light-Controlled Intracellular Heating and Nanoscale Temperature Sensing.

Temperature is an essential parameter in all biological systems, but information about the actual temperature in living cells is limited. Especially, in photothermal therapy, local intracellular temperature changes induce cell death but the local temperature gradients are not known. Highly sensitive nanothermometers would be required to measure and report local temperature changes independent of the intracellular environment, including pH or ions. Fluorescent nanodiamonds (ND) enable temperature sensing at the nanoscale independent of external conditions. Herein, we prepare ND nanothermometers coated with a nanogel shell and the photothermal agent indocyanine green serves as a heat generator and sensor. Upon irradiation, programmed cell death was induced in cancer cells with high spatial control. In parallel, the increase in local temperature was recorded by the ND nanothermometers. This approach represents a great step forward to record local temperature changes in different cellular environments inside cells and correlate these with thermal biology.

Human α-Defensin-6 Neutralizes Clostridioides difficile Toxins TcdA and TcdB by Direct Binding.

Rising incidences and mortalities have drawn attention to Clostridioides difficile infections (CDIs) in recent years. The main virulence factors of this bacterium are the exotoxins TcdA and TcdB, which glucosylate Rho-GTPases and thereby inhibit Rho/actin-mediated processes in cells. This results in cell rounding, gut barrier disruption and characteristic clinical symptoms. So far, treatment of CDIs is limited and mainly restricted to some antibiotics, often leading to a vicious circle of antibiotic-induced disease recurrence. Here, we demonstrate the protective effect of the human antimicrobial peptide α-defensin-6 against TcdA, TcdB and the combination of both toxins in vitro and in vivo and unravel the underlying molecular mechanism. The defensin prevented toxin-mediated glucosylation of Rho-GTPases in cells and protected human cells, model epithelial barriers as well as zebrafish embryos from toxic effects. In vitro analyses revealed direct binding to TcdB in an SPR approach and the rapid formation of TcdB/α-defensin-6 complexes, as analyzed with fluorescent TcdB by time-lapse microscopy. In conclusion, the results imply that α-defensin-6 rapidly sequesters the toxin into complexes, which prevents its cytotoxic activity. These findings extend the understanding of how human peptides neutralize bacterial protein toxins and might be a starting point for the development of novel therapeutic options against CDIs.

Antimicrobial Efficiency of Chitosan and Its Methylated Derivative against Lentilactobacillus parabuchneri Biofilms.

Antimicrobial materials are considered potential alternatives to prevent the development of biofilm-associated contaminations. Concerns regarding synthetic preservatives necessitate the development of innovative and safe natural antimicrobials. In the present study, we discuss the in situ infrared attenuated total reflection spectroscopy (IR-ATR) investigations of the selective antimicrobial efficiency of chitosan in controlling the growth of Lentilactobacillus parabuchneri biofilms. The protonated charges of chitosan were additionally amplified by structural modification via methylation, yielding quaternized derivative TMC (i.e., N, N, N-trimethyl chitosan). To evaluate antimicrobial effectiveness against L. parab. biofilms, IR-ATR spectroscopy provided information on molecular mechanisms and insights into chemical changes during real-time biofilm inhibition studies. The integrated fiberoptic oxygen microsensors enabled monitoring oxygen (O2) concentration gradients within biofilms, thereby confirming the metabolic oxygen depletion dropping from 4.5 to 0.7 mg L-1. IR studies revealed strong electrostatic interactions between chitosan/its water-soluble derivative and bacteria, indicating that a few hours were sufficient to affect biofilm disruption. The significant decrease in the IR bands is related to the characteristic spectral information of amide I, II, III, nucleic acid, and extracellular polymeric matrix (EPS) produced by L. parabuchneri biofilms. Cell clusters of biofilms, microcolonies, and destabilization of the EPS matrix after the addition of biopolymers were visualized using optical microscopy. In addition, scanning electron microscopy (SEM) of biofilms grown on polystyrene and stainless-steel surfaces was used to examine morphological changes, indicating the disintegration of the biofilm matrix into individual cells. Quantification of the total biofilm formation correlated with the CV assay results, indicating cell death and lysis. The electrostatic interactions between chitosan and the bacterial cell wall typically occur between protonated amino groups and negatively charged phospholipids, which promote permeabilization. Biofilm growth inhibition was assessed by a viability assay for a period of 72 h and in the range of low MIC values (varying 0.01-2%). These results support the potential of chitosan and TMC for bacterial growth prevention of the foodborne contaminant L. parabuchneri in the dairy industry and for further implementation in food packaging.

Human peptide α-defensin-1 interferes with Clostridioides difficile toxins TcdA, TcdB, and CDT.

The human pathogenic bacterium Clostridioides difficile produces two exotoxins TcdA and TcdB, which inactivate Rho GTPases thereby causing C. difficile-associated diseases (CDAD) including life-threatening pseudomembranous colitis. Hypervirulent strains produce additionally the binary actin ADP-ribosylating toxin CDT. These strains are hallmarked by more severe forms of CDAD and increased frequency and severity. Once in the cytosol, the toxins act as enzymes resulting in the typical clinical symptoms. Therefore, targeting and inactivation of the released toxins are of peculiar interest. Prompted by earlier findings that human α-defensin-1 neutralizes TcdB, we investigated the effects of the defensin on all three C. difficile toxins. Inhibition of TcdA, TcdB, and CDT was demonstrated by analyzing toxin-induced changes in cell morphology, substrate modification, and decrease in transepithelial electrical resistance. Application of α-defensin-1 protected cells and human intestinal organoids from the cytotoxic effects of TcdA, TcdB, CDT, and their combination which is attributed to a direct interaction between the toxins and α-defensin-1. In mice, the application of α-defensin-1 reduced the TcdA-induced damage of intestinal loops in vivo. In conclusion, human α-defensin-1 is a specific and potent inhibitor of the C. difficile toxins and a promising agent to develop novel therapeutic options against C. difficile infections.

A novel rabbit derived anti-HER2 antibody with pronounced therapeutic effectiveness on HER2-positive breast cancer cells in vitro and in humanized tumor mice (HTM).

BACKGROUND: Antibody based cancer therapies have achieved convincing success rates combining enhanced tumor specificity and reduced side effects in patients. Trastuzumab that targets the human epidermal growth factor related receptor 2 (HER2) is one of the greatest success stories in this field. For decades, trastuzumab based treatment regimens are significantly improving the prognosis of HER2-positive breast cancer patients both in the metastatic and the (neo-) adjuvant setting. Nevertheless, ≥ 50% of trastuzumab treated patients experience de-novo or acquired resistance. Therefore, an enhanced anti-HER2 targeting with improved treatment efficiency is still aspired. METHODS: Here, we determined cellular and molecular mechanisms involved in the treatment of HER2-positive BC cells with a new rabbit derived HER2 specific chimeric monoclonal antibody called "B100″. We evaluated the B100 treatment efficiency of HER2-positive BC cells with different sensitivity to trastuzumab both in vitro and in the presence of a human immune system in humanized tumor mice. RESULTS: B100 not only efficiently blocks cell proliferation but more importantly induces apoptotic tumor cell death. Detailed in vitro analyses of B100 in comparison to trastuzumab (and pertuzumab) revealed equivalent HER2 internalization and recycling capacity, similar Fc receptor signaling, but different HER2 epitope recognition with high binding and treatment efficiency. In trastuzumab resistant SK-BR-3 based humanized tumor mice the B100 treatment eliminated the primary tumor but even more importantly eradicated metastasized tumor cells in lung, liver, brain, and bone marrow. CONCLUSION: Overall, B100 demonstrated an enhanced anti-tumor activity both in vitro and in an enhanced preclinical HTM in vivo model compared to trastuzumab or pertuzumab. Thus, the use of B100 is a promising option to complement and to enhance established treatment regimens for HER2-positive (breast) cancer and to overcome trastuzumab resistance. Extended preclinical analyses using appropriate models and clinical investigations are warranted.

ABC transporters in gills of rainbow trout (Oncorhynchus mykiss).

Fish gills are a structurally and functionally complex organ at the interface between the organism and the aquatic environment. Gill functions include the transfer of organic molecules, both natural ones and xenobiotic compounds. Whether the branchial exchange of organic molecules involves active transporters is currently not known. Here, we investigated the presence, diversity and functional activity of ATP-binding cassette (ABC) transporters in gills of juvenile rainbow trout. By means of RT-qPCR, gene transcripts of members from the abcb, abcc and abcg subfamilies were identified. Comparisons with mRNA profiles from trout liver and kidney revealed that ABC transporters known to have an apical localization in polarized epithelia, especially abcc2 and abcb1, were under-represented in the gills. In contrast, ABC transporters with mainly basolateral localization showed comparable gene transcript levels in the three organs. The most prominent ABC transporter in gills was an abcb subfamily member, which was annotated as abcb5 based on the synteny and phylogeny. Functional in vivo assays pointed to a role of branchial ABC transporters in branchial solute exchange. We further assessed the utility of primary gill cell cultures to characterize transporter-mediated branchial exchange of organic molecules, by examining ABC transporter gene transcript patterns and functional activity in primary cultures. The gill cultures displayed functional transport activity, but the ABC mRNA expression patterns were different to those of the intact gills. Overall, the findings of this study provide evidence for the presence of functional ABC transporter activity in gills of fish.