Carbonic anhydrases in metazoan model organisms: molecules, mechanisms, and physiology.

During the past three decades, mice, zebrafish, fruit flies, and Caenorhabditis elegans have been the primary model organisms used for the study of various biological phenomena. These models have also been adopted and developed to investigate the physiological roles of carbonic anhydrases (CAs) and carbonic anhydrase-related proteins (CARPs). These proteins belong to eight CA families and are identified by Greek letters: α, ß, γ, δ, ζ, η, θ, and ι. Studies using model organisms have focused on two CA families, α-CAs and ß-CAs, which are expressed in both prokaryotic and eukaryotic organisms with species-specific distribution patterns and unique functions. This review covers the biological roles of CAs and CARPs in light of investigations performed in model organisms. Functional studies demonstrate that CAs are not only linked to the regulation of pH homeostasis, the classical role of CAs, but also contribute to a plethora of previously undescribed functions.

Strategies for dissecting the complexity of neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) are associated with a wide range of clinical features, affecting multiple pathways involved in brain development and function. Recent advances in high-throughput sequencing have unveiled numerous genetic variants associated with NDDs, which further contribute to disease complexity and make it challenging to infer disease causation and underlying mechanisms. Herein, we review current strategies for dissecting the complexity of NDDs using model organisms, induced pluripotent stem cells, single-cell sequencing technologies, and massively parallel reporter assays. We further highlight single-cell CRISPR-based screening techniques that allow genomic investigation of cellular transcriptomes with high efficiency, accuracy, and throughput. Overall, we provide an integrated review of experimental approaches that can be applicable for investigating a broad range of complex disorders.

Transcriptomic congruence analysis for evaluating model organisms.

Model organisms are instrumental substitutes for human studies to expedite basic, translational, and clinical research. Despite their indispensable role in mechanistic investigation and drug development, molecular congruence of animal models to humans has long been questioned and debated. Little effort has been made for an objective quantification and mechanistic exploration of a model organism's resemblance to humans in terms of molecular response under disease or drug treatment. We hereby propose a framework, namely Congruence Analysis for Model Organisms (CAMO), for transcriptomic response analysis by developing threshold-free differential expression analysis, quantitative concordance/discordance scores incorporating data variabilities, pathway-centric downstream investigation, knowledge retrieval by text mining, and topological gene module detection for hypothesis generation. Instead of a genome-wide vague and dichotomous answer of "poorly" or "greatly" mimicking humans, CAMO assists researchers to numerically quantify congruence, to dissect true cross-species differences from unwanted biological or cohort variabilities, and to visually identify molecular mechanisms and pathway subnetworks that are best or least mimicked by model organisms, which altogether provides foundations for hypothesis generation and subsequent translational decisions.

Pathogenic Rickettsia spp. as emerging models for bacterial biology.

Our understanding of free-living bacterial models like Escherichia coli far outpaces that of obligate intracellular bacteria, which cannot be cultured axenically. All obligate intracellular bacteria are host-associated, and many cause serious human diseases. Their constant exposure to the distinct biochemical niche of the host has driven the evolution of numerous specialized bacteriological and genetic adaptations, as well as innovative molecular mechanisms of infection. Here, we review the history and use of pathogenic Rickettsia species, which cause an array of vector-borne vascular illnesses, as model systems to probe microbial biology. Although many challenges remain in our studies of these organisms, the rich pathogenic and biological diversity of Rickettsia spp. constitutes a unique backdrop to investigate how microbes survive and thrive in host and vector cells. We take a bacterial-focused perspective and highlight emerging insights that relate to new host-pathogen interactions, bacterial physiology, and evolution. The transformation of Rickettsia spp. from pathogens to models demonstrates how recalcitrant microbes may be leveraged in the lab to tap unmined bacterial diversity for new discoveries. Rickettsia spp. hold great promise as model systems not only to understand other obligate intracellular pathogens but also to discover new biology across and beyond bacteria.

Biological puzzles solved by using Streptococcus pneumoniae: a historical review of the pneumococcal studies that have impacted medicine and shaped molecular bacteriology.

The major human pathogen Streptococcus pneumoniae has been the subject of intensive clinical and basic scientific study for over 140 years. In multiple instances, these efforts have resulted in major breakthroughs in our understanding of basic biological principles as well as fundamental tenets of bacterial pathogenesis, immunology, vaccinology, and genetics. Discoveries made with S. pneumoniae have led to multiple major public health victories that have saved the lives of millions. Studies on S. pneumoniae continue today, where this bacterium is being used to dissect the impact of the host on disease processes, as a powerful cell biology model, and to better understand the consequence of human actions on commensal bacteria at the population level. Herein we review the major findings, i.e., puzzle pieces, made with S. pneumoniae and how, over the years, they have come together to shape our understanding of this bacterium's biology and the practice of medicine and modern molecular biology.

DNA-protein quasi-mapping for rapid differential gene expression analysis in non-model organisms.

BACKGROUND: Conventional differential gene expression analysis pipelines for non-model organisms require computationally expensive transcriptome assembly. We recently proposed an alternative strategy of directly aligning RNA-seq reads to a protein database, and demonstrated drastic improvements in speed, memory usage, and accuracy in identifying differentially expressed genes. RESULT: Here we report a further speed-up by replacing DNA-protein alignment by quasi-mapping, making our pipeline > 1000× faster than assembly-based approach, and still more accurate. We also compare quasi-mapping to other mapping techniques, and show that it is faster but at the cost of sensitivity. CONCLUSION: We provide a quick-and-dirty differential gene expression analysis pipeline for non-model organisms without a reference transcriptome, which directly quasi-maps RNA-seq reads to a reference protein database, avoiding computationally expensive transcriptome assembly.

Long-read de novo genome assembly of Gulf toadfish (Opsanus beta).

BACKGROUND: The family Batrachoididae are a group of ecologically important teleost fishes with unique life histories, behavior, and physiology that has made them popular model organisms. Batrachoididae remain understudied in the realm of genomics, with only four reference genome assemblies available for the family, with three being highly fragmented and not up to current assembly standards. Among these is the Gulf toadfish, Opsanus beta, a model organism for serotonin physiology which has recently been bred in captivity. RESULTS: Here we present a new, de novo genome and transcriptome assemblies for the Gulf toadfish using PacBio long read technology. The genome size of the final assembly is 2.1 gigabases, which is among the largest teleost genomes. This new assembly improves significantly upon the currently available reference for Opsanus beta with a final scaffold count of 62, of which 23 are chromosome scale, an N50 of 98,402,768, and a BUSCO completeness score of 97.3%. Annotation with ab initio and transcriptome-based methods generated 41,076 gene models. The genome is highly repetitive, with ~ 70% of the genome composed of simple repeats and transposable elements. Satellite DNA analysis identified potential telomeric and centromeric regions. CONCLUSIONS: This improved assembly represents a valuable resource for future research using this important model organism and to teleost genomics more broadly.

miRPreM and tiRPreM: Improved methodologies for the prediction of miRNAs and tRNA-induced small non-coding RNAs for model and non-model organisms.

In recent years, microRNAs (miRNAs) and tRNA-derived RNA fragments (tRFs) have been reported extensively following different approaches of identification and analysis. Comprehensively analyzing the present approaches to overcome the existing variations, we developed a benchmarking methodology each for the identification of miRNAs and tRFs, termed as miRNA Prediction Methodology (miRPreM) and tRNA-induced small non-coding RNA Prediction Methodology (tiRPreM), respectively. We emphasized the use of respective genome of organism under study for mapping reads, sample data with at least two biological replicates, normalized read count support and novel miRNA prediction by two standard tools with multiple runs. The performance of these methodologies was evaluated by using Oryza coarctata, a wild rice species as a case study for model and non-model organisms. With organism-specific reference genome approach, 98 miRNAs and 60 tRFs were exclusively found. We observed high accuracy (13 out of 15) when tested these genome-specific miRNAs in support of analyzing the data with respective organism. Such a strong impact of miRPreM, we have predicted more than double number of miRNAs (186) as compared with the traditional approaches (79) and with tiRPreM, we have predicted all known classes of tRFs within the same small RNA data. Moreover, the methodologies presented here are in standard form in order to extend its applicability to different organisms rather than restricting to plants. Hence, miRPreM and tiRPreM can fulfill the need of a comprehensive methodology for miRNA prediction and tRF identification, respectively, for model and non-model organisms.

AI-based automated construction of high-precision Geobacillus thermoglucosidasius enzyme constraint model.

Geobacillus thermoglucosidasius NCIMB 11955 possesses advantages, such as high-temperature tolerance, rapid growth rate, and low contamination risk. Additionally, it features efficient gene editing tools, making it one of the most promising next-generation cell factories. However, as a non-model microorganism, a lack of metabolic information significantly hampers the construction of high-precision metabolic flux models. Here, we propose a BioIntelliModel (BIM) strategy based on artificial intelligence technology for the automated construction of enzyme-constrained models. 1). BIM utilises the Contrastive Learning Enabled Enzyme Annotation (CLEAN) prediction tool to analyse the entire genome sequence of G. thermoglucosidasius NCIMB 11955, uncovering potential functional proteins in non-model strains. 2). The MetaPatchM module of BIM automates the repair of the metabolic network model. 3). The Tianjin University of Science and Technology-kcat (TUST-kcat) module predicts the kcat values of enzymes within the model. 4). The Enzyme-insert procedure constructs an enzyme-constrained model and performs a global scan to address overconstraint issues. Enzymatic data were automatically integrated into the metabolic flux model, creating an enzyme-constrained model, ec_G-ther11955. To validate model accuracy, we used both the p-thermo and ec_G-ther11955 models to predict riboflavin production strategies. The ec_G-ther11955 model demonstrated significantly higher accuracy. To further verify its efficacy, we employed ec_G-ther11955 to guide the rational design of L-valine-producing strains. Using the Optimisation Procedure for Identifying All Genetic Manipulations Leading to Targeted Overproductions (OptForce), Predictive Knockout Targeting (PKT), and Flux Scanning based on Enforced Objective Flux (FSEOF) algorithms, we identified 24 knockout and overexpression targets, achieving an accuracy rate of 87.5%. Ultimately, this led to an increase of 664.04% in L-valine titre. This study provides a novel strategy for rapidly constructing non-model strain models and demonstrates the tremendous potential of artificial intelligence in metabolic engineering.

Biosensors for the detection of chorismate and cis,cis-muconic acid in Corynebacterium glutamicum.

Corynebacterium glutamicum ATCC 13032 is a promising microbial chassis for industrial production of valuable compounds, including aromatic amino acids derived from the shikimate pathway. In this work, we developed two whole-cell, transcription factor based fluorescent biosensors to track cis,cis-muconic acid (ccMA) and chorismate in C. glutamicum. Chorismate is a key intermediate in the shikimate pathway from which value-added chemicals can be produced, and a shunt from the shikimate pathway can divert carbon to ccMA, a high value chemical. We transferred a ccMA-inducible transcription factor, CatM, from Acinetobacter baylyi ADP1 into C. glutamicum and screened a promoter library to isolate variants with high sensitivity and dynamic range to ccMA by providing benzoate, which is converted to ccMA intracellularly. The biosensor also detected exogenously supplied ccMA, suggesting the presence of a putative ccMA transporter in C. glutamicum, though the external ccMA concentration threshold to elicit a response was 100-fold higher than the concentration of benzoate required to do so through intracellular ccMA production. We then developed a chorismate biosensor, in which a chorismate inducible promoter regulated by natively expressed QsuR was optimized to exhibit a dose-dependent response to exogenously supplemented quinate (a chorismate precursor). A chorismate-pyruvate lyase encoding gene, ubiC, was introduced into C. glutamicum to lower the intracellular chorismate pool, which resulted in loss of dose dependence to quinate. Further, a knockout strain that blocked the conversion of quinate to chorismate also resulted in absence of dose dependence to quinate, validating that the chorismate biosensor is specific to intracellular chorismate pool. The ccMA and chorismate biosensors were dually inserted into C. glutamicum to simultaneously detect intracellularly produced chorismate and ccMA. Biosensors, such as those developed in this study, can be applied in C. glutamicum for multiplex sensing to expedite pathway design and optimization through metabolic engineering in this promising chassis organism. ONE-SENTENCE SUMMARY: High-throughput screening of promoter libraries in Corynebacterium glutamicum to establish transcription factor based biosensors for key metabolic intermediates in shikimate and ß-ketoadipate pathways.

Whole-genome sequencing analysis of volvocine green algae reveals the molecular genetic basis for the diversity and evolution of sex.

This review describes the development of evolutionary studies of sex based on the volvocine lineage of green algae, which was facilitated by whole-genome analyses of both model and non-model species. Volvocine algae, which include Chlamydomonas and Volvox species, have long been considered a model group for experimental studies investigating the evolution of sex. Thus, whole-genomic information on the sex-determining regions of volvocine algal sex chromosomes has been sought to elucidate the molecular genetic basis of sex evolution. By 2010, whole genomes were published for two model species in this group, Chlamydomonas reinhardtii and Volvox carteri. Recent improvements in sequencing technology, particularly next-generation sequencing, allowed our studies to obtain complete genomes for non-model, but evolutionary important, volvocine algal species. These genomes have provided critical details about sex-determining regions that will contribute to our understanding of the diversity and evolution of sex.

DNA adduct formation in Saccharomyces cerevisiae following exposure to environmental pollutants, as in vivo model for molecular toxicity studies.

DNA adduction in the model yeast Saccharomyces cerevisiae was investigated after exposure to the fungicide penconazole and the reference genotoxic compound benzo(a)pyrene, for validating yeasts as a tool for molecular toxicity studies, particularly of environmental pollution. The effect of the toxicants on the yeast's growth kinetics was determined as an indicator of cytotoxicity. Fermentative cultures of S. cerevisiae were exposed to 2 ppm of Penconazole during different phases of growth; while 0.2 and 2 ppm of benzo(a)pyrene were applied to the culture medium before inoculation and on exponential cultures. Exponential respiratory cultures were also exposed to 0.2 ppm of B(a)P for comparison of both metabolisms. Penconazole induced DNA adducts formation in the exponential phase test; DNA adducts showed a peak of 54.93 adducts/109 nucleotides. Benzo(a)pyrene induced the formation of DNA adducts in all the tests carried out; the highest amount of 46.7 adducts/109 nucleotides was obtained in the fermentative cultures after the exponential phase exposure to 0.2 ppm; whereas in the respiratory cultures, 14.6 adducts/109 nucleotides were detected. No cytotoxicity was obtained in any experiment. Our study showed that yeast could be used to analyse DNA adducts as biomarkers of exposure to environmental toxicants.

Synchronized Swarmers and Sticky Stalks: Caulobacter crescentus as a Model for Bacterial Cell Biology.

First isolated and classified in the 1960s, Caulobacter crescentus has been instrumental in the study of bacterial cell biology and differentiation. C. crescentus is a Gram-negative alphaproteobacterium that exhibits a dimorphic life cycle composed of two distinct cell types: a motile swarmer cell and a nonmotile, division-competent stalked cell. Progression through the cell cycle is accentuated by tightly controlled biogenesis of appendages, morphological transitions, and distinct localization of developmental regulators. These features as well as the ability to synchronize populations of cells and follow their progression make C. crescentus an ideal model for answering questions relevant to how development and differentiation are achieved at the single-cell level. This review will explore the discovery and development of C. crescentus as a model organism before diving into several key features and discoveries that have made it such a powerful organism to study. Finally, we will summarize a few of the ongoing areas of research that are leveraging knowledge gained over the last century with C. crescentus to highlight its continuing role at the forefront of cell and developmental biology.

Bioprospecting the American Alligator Peptidome for antiviral peptides against Venezuelan equine encephalitis virus.

The innate immune protection provided by cationic antimicrobial peptides (CAMPs) has been shown to extend to antiviral activity, with putative mechanisms of action including direct interaction with host cells or pathogen membranes. The lack of therapeutics available for the treatment of viruses such as Venezuelan equine encephalitis virus (VEEV) underscores the urgency of novel strategies for antiviral discovery. American alligator plasma has been shown to exhibit strong in vitro antibacterial activity, and functionalized hydrogel particles have been successfully employed for the identification of specific CAMPs from alligator plasma. Here, a novel bait strategy in which particles were encapsulated in membranes from either healthy or VEEV-infected cells was implemented to identify peptides preferentially targeting infected cells for subsequent evaluation of antiviral activity. Statistical analysis of peptide identification results was used to select five candidate peptides for testing, of which one exhibited a dose-dependent inhibition of VEEV and also significantly inhibited infectious titers. Results suggest our bioprospecting strategy provides a versatile platform that may be adapted for antiviral peptide identification from complex biological samples.

Systematically identifying genetic signatures including novel SNP-clusters, nonsense variants, frame-shift INDELs, and long STR expansions that potentially link to unknown phenotypes existing in dog breeds.

BACKGROUND: In light of previous studies that profiled breed-specific traits or used genome-wide association studies to refine loci associated with characteristic morphological features in dogs, the field has gained tremendous genetic insights for known dog traits observed among breeds. Here we aim to address the question from a reserve perspective: whether there are breed-specific genotypes that may underlie currently unknown phenotypes. This study provides a complete set of breed-specific genetic signatures (BSGS). Several novel BSGS with significant protein-altering effects were highlighted and validated. RESULTS: Using the next generation whole-genome sequencing technology coupled with unsupervised machine learning for pattern recognitions, we constructed and analyzed a high-resolution sequence map for 76 breeds of 412 dogs. Genomic structures including novel single nucleotide polymorphisms (SNPs), SNP clusters, insertions, deletions (INDELs) and short tandem repeats (STRs) were uncovered mutually exclusively among breeds. We also partially validated some novel nonsense variants by Sanger sequencing with additional dogs. Four novel nonsense BSGS were found in the Bernese Mountain Dog, Samoyed, Bull Terrier, and Basset Hound, respectively. Four INDELs resulting in either frame-shift or codon disruptions were found in the Norwich Terrier, Airedale Terrier, Chow Chow and Bernese Mountain Dog, respectively. A total of 15 genomic regions containing three types of BSGS (SNP-clusters, INDELs and STRs) were identified in the Akita, Alaskan Malamute, Chow Chow, Field Spaniel, Keeshond, Shetland Sheepdog and Sussex Spaniel, in which Keeshond and Sussex Spaniel each carried one amino-acid changing BSGS in such regions. CONCLUSION: Given the strong relationship between human and dog breed-specific traits, this study might be of considerable interest to researchers and all. Novel genetic signatures that can differentiate dog breeds were uncovered. Several functional genetic signatures might indicate potentially breed-specific unknown phenotypic traits or disease predispositions. These results open the door for further investigations. Importantly, the computational tools we developed can be applied to any dog breeds as well as other species. This study will stimulate new thinking, as the results of breed-specific genetic signatures may offer an overarching relevance of the animal models to human health and disease.

Down, then up: non-parallel genome size changes and a descending chromosome series in a recent radiation of the Australian allotetraploid plant species, Nicotiana section Suaveolentes (Solanaceae).

BACKGROUND AND AIMS: The extent to which genome size and chromosome numbers evolve in concert is little understood, particularly after polyploidy (whole-genome duplication), when a genome returns to a diploid-like condition (diploidization). We study this phenomenon in 46 species of allotetraploid Nicotiana section Suaveolentes (Solanaceae), which formed <6 million years ago and radiated in the arid centre of Australia. METHODS: We analysed newly assessed genome sizes and chromosome numbers within the context of a restriction site-associated nuclear DNA (RADseq) phylogenetic framework. KEY RESULTS: RADseq generated a well-supported phylogenetic tree, in which multiple accessions from each species formed unique genetic clusters. Chromosome numbers and genome sizes vary from n = 2x = 15 to 24 and 2.7 to 5.8 pg/1C nucleus, respectively. Decreases in both genome size and chromosome number occur, although neither consistently nor in parallel. Species with the lowest chromosome numbers (n = 15-18) do not possess the smallest genome sizes and, although N. heterantha has retained the ancestral chromosome complement, n = 2x = 24, it nonetheless has the smallest genome size, even smaller than that of the modern representatives of ancestral diploids. CONCLUSIONS: The results indicate that decreases in genome size and chromosome number occur in parallel down to a chromosome number threshold, n = 20, below which genome size increases, a phenomenon potentially explained by decreasing rates of recombination over fewer chromosomes. We hypothesize that, more generally in plants, major decreases in genome size post-polyploidization take place while chromosome numbers are still high because in these stages elimination of retrotransposons and other repetitive elements is more efficient. Once such major genome size change has been accomplished, then dysploid chromosome reductions take place to reorganize these smaller genomes, producing species with small genomes and low chromosome numbers such as those observed in many annual angiosperms, including Arabidopsis.

Insights into human kidney function from the study of Drosophila.

Biological and biomedical research using Drosophila melanogaster as a model organism has gained recognition through several Nobel prizes within the last 100 years. Drosophila exhibits several advantages when compared to other in vivo models such as mice and rats, as its life cycle is very short, animal maintenance is easy and inexpensive and a huge variety of transgenic strains and tools are publicly available. Moreover, more than 70% of human disease-causing genes are highly conserved in the fruit fly. Here, we explain the use of Drosophila in nephrology research and describe two kidney tissues, Malpighian tubules and the nephrocytes. The latter are the homologous cells to mammalian glomerular podocytes and helped to provide insights into a variety of signaling pathways due to the high morphological similarities and the conserved molecular make-up between nephrocytes and podocytes. In recent years, nephrocytes have also been used to study inter-organ communication as links between nephrocytes and the heart, the immune system and the muscles have been described. In addition, other tissues such as the eye and the reproductive system can be used to study the functional role of proteins being part of the kidney filtration barrier.

Ulva: An emerging green seaweed model for systems biology.

Green seaweeds exhibit a wide range of morphologies and occupy various ecological niches, spanning from freshwater to marine and terrestrial habitats. These organisms, which predominantly belong to the class Ulvophyceae, showcase a remarkable instance of parallel evolution toward complex multicellularity and macroscopic thalli in the Viridiplantae lineage. Within the green seaweeds, several Ulva species ("sea lettuce") are model organisms for studying carbon assimilation, interactions with bacteria, life cycle progression, and morphogenesis. Ulva species are also notorious for their fast growth and capacity to dominate nutrient-rich, anthropogenically disturbed coastal ecosystems during "green tide" blooms. From an economic perspective, Ulva has garnered increasing attention as a promising feedstock for the production of food, feed, and biobased products, also as a means of removing excess nutrients from the environment. We propose that Ulva is poised to further develop as a model in green seaweed research. In this perspective, we focus explicitly on Ulva mutabilis/compressa as a model species and highlight the molecular data and tools that are currently available or in development. We discuss several areas that will benefit from future research or where exciting new developments have been reported in other Ulva species.

Screening the immunotoxicity of different food preservative agents on the model organism Galleria mellonella L. (Lepidoptera: Pyralidae) larvae.

Immunotoxic effects of sodium benzoate (SB, E211), sodium nitrate (SNa, E251), and sodium nitrite (SNi, E250), a few of the most common food preservatives, on the model organism Galleria mellonella L. (Lepidoptera: Pyralidae) larvae were investigated in this study. The last instar larvae were used for all experimental analyses. For this purpose, median lethal doses of SB, SNa, and SNi were applied to the larvae by the force-feeding method. We found that force-feeding G. mellonella larvae with SB, SNa, and SNi significantly reduced the larval total hemocyte counts, prohemocyte, and granulocyte ratios but increased plasmatocyte, spherulocyte, and oenocyte ratios, as well as the hemocyte mitotic indices and micronucleus frequency. The spreading ability of hemocytes and hemocyte-mediated immune responses were lower in the SB, SNa-, and SNi-treated larval groups compared to controls. Apoptotic indices were higher in all larval groups treated with food preservatives, but increments in necrotic indices were only significantly higher in SNi-treated larvae compared to controls. Our research shows that SB, SNa, and SNi have immunotoxic and cytotoxic potential on G. mellonella larvae. Thus, we suggest that G. mellonella larvae can be used as preliminary in vivo models to screen the immunotoxic effects of food preservative agents.

Substrate colour guides turquoise killifish's (Nothobranchius furzeri) choice of preferred spawning habitat.

Turquoise killifish (Nothobranchius furzeri) is a promising new model species used in biomedical and ecological laboratory experiments, and should be kept under optimal conditions to ensure fish welfare and the quality of science. While the popularity of this model species is rapidly increasing, we need to improve our understanding of how the species interacts with its environment to optimize its husbandry. Specifically, turquoise killifish are substrate spawners that bury their eggs in the sediment, which can be accommodated under captive conditions, but it is not yet known whether or not turquoise killifish have a preference for a specific sediment colour. Here, we performed a laboratory experiment in which fish could choose between white, orange and black sand for spawning, colours which are relevant in both laboratory and field conditions. We assessed their preference in the context of single breeding pairs, as well as in a social group setting. Additionally, we also assessed the preference of individuals for a white versus black background in a nonmating context. Single breeding pairs deposited over 3.5 times more eggs in black compared to orange or white sand. Similarly, fish in social groups deposited over 3.5 times more eggs in black compared to orange sand, which in turn was over two times higher than that in white sand. Fish showed a slight preference for the black compared to the white zone in a nonmating context, but this did not correlate with substrate choice during the spawning tests. The results suggest that turquoise killifish select their preferred spawning location based on the colour of the substrate. These findings contribute to our understanding of the species' biology and can help to guide good welfare and scientific practice.