Comparison between the gut bacterial community of laboratory cultured and wild Daphnia.

The fitness of an organism is often impacted by the composition and biological activity of its associated bacterial community. Many factors, including host genetics, diet, and temperature can influence the bacterial community composition. Furthermore, these factors can differ strongly between natural and laboratory environments. Consequently, several studies have highlighted results from laboratory experiments investigating host-associated bacterial communities to be conflicting with those obtained under field conditions. Here, we compared the Daphnia magna gut bacterial communities in natural host populations with those of laboratory cultured hosts. We further analyzed changes in the gut bacterial communities after transferring hosts from natural populations to the laboratory on the short- and long-term. Results show that, in general, the gut bacterial communities from natural populations differ from those of laboratory cultures and that their composition and diversity changed one hour after being transferred to the laboratory. Over the following 14 days, the composition and diversity changed gradually. On the longer term (after two years of rearing hosts in the laboratory) the composition and diversity of the gut bacterial communities was strongly altered compared to the initial state. Our findings indicate that the gut bacterial communities of Daphnia magna in laboratory experiments is not representative for natural field conditions, and that caution should be taken when interpreting results from laboratory experiments for natural settings.

Hypermutator emergence in experimental Escherichia coli populations is stress-type dependent.

Genotypes exhibiting an increased mutation rate, called hypermutators, can propagate in microbial populations because they can have an advantage due to the higher supply of beneficial mutations needed for adaptation. Although this is a frequently observed phenomenon in natural and laboratory populations, little is known about the influence of parameters such as the degree of maladaptation, stress intensity, and the genetic architecture for adaptation on the emergence of hypermutators. To address this knowledge gap, we measured the emergence of hypermutators over ~1,000 generations in experimental Escherichia coli populations exposed to different levels of osmotic or antibiotic stress. Our stress types were chosen based on the assumption that the genetic architecture for adaptation differs between them. Indeed, we show that the size of the genetic basis for adaptation is larger for osmotic stress compared to antibiotic stress. During our experiment, we observed an increased emergence of hypermutators in populations exposed to osmotic stress but not in those exposed to antibiotic stress, indicating that hypermutator emergence rates are stress type dependent. These results support our hypothesis that hypermutator emergence is linked to the size of the genetic basis for adaptation. In addition, we identified other parameters that covaried with stress type (stress level and IS transposition rates) that might have contributed to an increased hypermutator provision and selection. Our results provide a first comparison of hypermutator emergence rates under varying stress conditions and point towards complex interactions of multiple stress-related factors on the evolution of mutation rates.

Neural network algorithm for detection of erosions and ankylosis on CT of the sacroiliac joints: multicentre development and validation of diagnostic accuracy.

OBJECTIVES: To evaluate the feasibility and diagnostic accuracy of a deep learning network for detection of structural lesions of sacroiliitis on multicentre pelvic CT scans. METHODS: Pelvic CT scans of 145 patients (81 female, 121 Ghent University/24 Alberta University, 18-87 years old, mean 40 ± 13 years, 2005-2021) with a clinical suspicion of sacroiliitis were retrospectively included. After manual sacroiliac joint (SIJ) segmentation and structural lesion annotation, a U-Net for SIJ segmentation and two separate convolutional neural networks (CNN) for erosion and ankylosis detection were trained. In-training validation and tenfold validation testing (U-Net-n = 10 × 58; CNN-n = 10 × 29) on a test dataset were performed to assess performance on a slice-by-slice and patient level (dice coefficient/accuracy/sensitivity/specificity/positive and negative predictive value/ROC AUC). Patient-level optimisation was applied to increase the performance regarding predefined statistical metrics. Gradient-weighted class activation mapping (Grad-CAM++) heatmap explainability analysis highlighted image parts with statistically important regions for algorithmic decisions. RESULTS: Regarding SIJ segmentation, a dice coefficient of 0.75 was obtained in the test dataset. For slice-by-slice structural lesion detection, a sensitivity/specificity/ROC AUC of 95%/89%/0.92 and 93%/91%/0.91 were obtained in the test dataset for erosion and ankylosis detection, respectively. For patient-level lesion detection after pipeline optimisation for predefined statistical metrics, a sensitivity/specificity of 95%/85% and 82%/97% were obtained for erosion and ankylosis detection, respectively. Grad-CAM++ explainability analysis highlighted cortical edges as focus for pipeline decisions. CONCLUSIONS: An optimised deep learning pipeline, including an explainability analysis, detects structural lesions of sacroiliitis on pelvic CT scans with excellent statistical performance on a slice-by-slice and patient level. CLINICAL RELEVANCE STATEMENT: An optimised deep learning pipeline, including a robust explainability analysis, detects structural lesions of sacroiliitis on pelvic CT scans with excellent statistical metrics on a slice-by-slice and patient level. KEY POINTS: • Structural lesions of sacroiliitis can be detected automatically in pelvic CT scans. • Both automatic segmentation and disease detection yield excellent statistical outcome metrics. • The algorithm takes decisions based on cortical edges, rendering an explainable solution.

Evolutionary responses to codon usage of horizontally transferred genes in Pseudomonas aeruginosa: gene retention, amelioration and compensatory evolution.

Prokaryote genome evolution is characterized by the frequent gain of genes through horizontal gene transfer (HGT). For a gene, being horizontally transferred can represent a strong change in its genomic and physiological context. If the codon usage of a transferred gene deviates from that of the receiving organism, the fitness benefits it provides can be reduced due to a mismatch with the expression machinery. Consequently, transferred genes with a deviating codon usage can be selected against or elicit evolutionary responses that enhance their integration, such as gene amelioration and compensatory evolution. Within bacterial species, the extent and relative importance of these different mechanisms has never been considered altogether. In this study, a phylogeny-based method was used to investigate the occurrence of these different evolutionary responses in Pseudomonas aeruginosa. Selection on codon usage of genes acquired through HGT was observed over evolutionary time, with the overall codon usage converging towards that of the core genome. Gene amelioration, through the accumulation of synonymous mutations after HGT, did not seem to systematically affect transferred genes. This pattern therefore seemed to be mainly driven by selective retention of transferred genes with an initial codon usage similar to that of the core genes. Additionally, variation in the copy number of tRNA genes was often associated with the acquisition of genes for which the observed variation could enhance their expression. This provides evidence that compensatory evolution might be an important mechanism for the integration of horizontally transferred genes.

Read between the Lines: Diversity of Nontranslational Selection Pressures on Local Codon Usage.

Protein coding genes can contain specific motifs within their nucleotide sequence that function as a signal for various biological pathways. The presence of such sequence motifs within a gene can have beneficial or detrimental effects on the phenotype and fitness of an organism, and this can lead to the enrichment or avoidance of this sequence motif. The degeneracy of the genetic code allows for the existence of alternative synonymous sequences that exclude or include these motifs, while keeping the encoded amino acid sequence intact. This implies that locally, there can be a selective pressure for preferentially using a codon over its synonymous alternative in order to avoid or enrich a specific sequence motif. This selective pressure could-in addition to mutation, drift and selection for translation efficiency and accuracy-contribute to shape the codon usage bias. In this review, we discuss patterns of avoidance of (or enrichment for) the various biological signals contained in specific nucleotide sequence motifs: transcription and translation initiation and termination signals, mRNA maturation signals, and antiviral immune system targets. Experimental data on the phenotypic or fitness effects of synonymous mutations in these sequence motifs confirm that they can be targets of local selection pressures on codon usage. We also formulate the hypothesis that transposable elements could have a similar impact on codon usage through their preferred integration sequences. Overall, selection on codon usage appears to be a combination of a global selection pressure imposed by the translation machinery, and a patchwork of local selection pressures related to biological signals contained in specific sequence motifs.

A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between Daphnia magna's gut microbiota and bacterioplankton.

The past 30 years have seen both a surge of interest in assessing ecological interactions using tools borrowed from network theory and an explosion of data on the occurrence of microbial symbionts thanks to next-generation sequencing. Given that classic network methods cannot currently measure the respective effects of different environmental and biological drivers on network structure, we here present two methods to elucidate the determinants of bipartite interaction networks. The first method is based on classifications and compares communities within networks to the grouping of nodes by treatment or similar controlling groups. The second method assesses the link between multivariate explanatory variables and network structure using redundancy analyses after singular value decomposition. In both methods, the significance of effects can be gauged through two randomizations. Our methods were applied to experimental data on Daphnia magna and its interactions with gut microbiota and bacterioplankton. The whole network was affected by Daphnia's diet (algae and/or cyanobacteria) and sample type, but not by Daphnia genotype. At coarse grains, bacterioplankton and gut microbiota communities were different. At this scale, the structure of the gut microbiota-based network was not linked to any explanatory factors, while the bacterioplankton-based network was related to both Daphnia's diet and genotype. At finer grains, Daphnia's diet and genotype affected both microbial networks, but the effect of diet on gut microbiota network structure was mediated solely by differences in microbial richness. While no reciprocal effect between the microbial communities could be found, fine-grained analyses presented a more nuanced picture, with bacterioplankton likely affecting the composition of the gut microbiota. Our methods are widely applicable to bipartite networks, can elucidate both controlled and environmental effects in experimental setting using a large amount of sequencing data and can tease apart reciprocal effects of networks on one another. The twofold approach we propose has the advantage of being able to tease apart effects at different scales of network structure, thus allowing for detailed assessment of reciprocal effects of linked networks on one another. As such, our network methods can help ecologists understand huge datasets reporting microbial co-occurrences within different hosts.

Isolation and identification of herbivorous ciliates from contaminated microalgal cultures.

Ciliates are a common but understudied group of grazers that can invade microalgal cultures. To estimate the potential impact of ciliates on microalgal culture productivity, the identification of species that can invade these cultures is essential. Furthermore, isolation of these herbivorous ciliates allows to use them in experiments that investigate the impact of ciliate grazing on the productivity of microalgal cultures. The main aims of this study were to isolate and identify ciliates that invade cultures of the freshwater microalgae Chlorella and Chlamydomonas, and to establish a live collection of these ciliates for usage in future experiments. To this end, we optimized a method for isolating ciliates from contaminated microalgal cultures and we developed a new PCR primer set for amplifying the partial 18S rDNA of ciliates belonging to the classes Spirotrichea, Oligohymenophorea and Colpodea. As a result, we isolated 11 ciliates from microalgal enrichment cultures inoculated with non-sterile dust and various freshwater sources. Of these 11 species, 7 were found to be feeding on Chlamydomonas. Ciliate species that fed on Chlorella could not be isolated in this study. Ciliate species feeding on Chlamydomonas were identified based on a combination of morphological observations and molecular analyses of partial 18S rDNA sequences.

The bacterioplankton community composition and a host genotype dependent occurrence of taxa shape the Daphnia magna gut bacterial community.

The assembly of host-associated bacterial communities is influenced by a multitude of biotic and abiotic factors. It is essential to gain insight in the impact and relative strength of these factors if we want to be able to predict the effects of environmental change on the assembly of host-associated bacterial communities, or deliberately modify them. The environmental pool of bacteria, from which the host is colonized, and the genetic background of the host are both considered to be important in determining the composition of host-associated bacterial communities. We experimentally assessed the relative importance of these two factors and their interaction on the composition of Daphnia magna gut bacterial communities. Bacterioplankton originating from natural ponds or a laboratory culture were used to inoculate germ-free Daphnia of different genotypes. We found that the composition of the environmental bacterial community has a major influence on the Daphnia gut bacterial community, both reflected by the presence or absence of specific taxa as well as by a correlation between abundances in the environment and on the host. Our data also indicate a consistent effect of host genotype on the occurrence of specific bacterial taxa in the gut of Daphnia over different environments.

Diet and Genotype of an Aquatic Invertebrate Affect the Composition of Free-Living Microbial Communities.

In spite of the growing interest in the role of the gut microbiome (GM) in host physiology and health, the mechanisms governing its assembly and its effects on the environment are poorly understood. In this article, we show that the host genotype and the GM of Daphnia influence the community structure of the surrounding bacterioplankton (BPK). When Daphnia genotypes were placed in an identical environment, both the GM and BPK showed a genotype and diet-dependent taxonomic composition. Overall, the GM strongly differed from the BPK in taxonomic composition and was characterized by a lower α-diversity, suggesting a selective rejecting of bacteria from the regional species pool. In a microbiome transplant experiment, the assembly of both the GM and BPK was strongly affected by the host genotype and the inoculum to which germ-free Daphnia were exposed. The combination of these results suggests a strong interaction between the host genotype, its GM and free-living microbial communities. Currently, it is generally assumed that an animal's diet has a strong effect on the animal's GM, but only a negligible (if any) effect on the surrounding environment. However, our results indicate that the diet/microbiome inocula have a small effect on the gut community and a large effect on the community in the surrounding environment. This structuring genotype × microbiome × environment effect is an essential prerequisite that could indicate that microbiomes play an important role in eco-evolutionary processes.

Microbiota inoculum composition affects holobiont assembly and host growth in Daphnia.

BACKGROUND: Host-associated microbiota is often acquired by horizontal transmission of microbes present in the environment. It is hypothesized that differences in the environmental pool of colonizers can influence microbiota community assembly on the host and as such affect holobiont composition and host fitness. To investigate this hypothesis, the host-associated microbiota of the invertebrate eco(toxico)logical model Daphnia was experimentally disturbed using different concentrations of the antibiotic oxytetracycline. The community assembly and host-microbiota interactions when Daphnia were colonized by the disturbed microbiota were investigated by inoculating germ-free individuals with the microbiota. RESULTS: Antibiotic-induced disturbance of the microbiota had a strong effect on the subsequent colonization of Daphnia by affecting ecological interactions between members of the microbiota. This resulted in differences in community assembly which, in turn, affected Daphnia growth. CONCLUSIONS: These results show that the composition of the pool of colonizing microbiota can be an important structuring factor of the microbiota assembly on Daphnia, affecting holobiont composition and host growth. These findings contribute to a better understanding of how the microbial environment can shape the holobiont composition and affect host-microbiota interactions.

Host-genotype dependent gut microbiota drives zooplankton tolerance to toxic cyanobacteria.

The gut microbiota impacts many aspects of its host's biology, and is increasingly considered as a key factor mediating performance of host individuals in continuously changing environments. Here we use gut microbiota transplants to show that both host genotype and gut microbiota mediate tolerance to toxic cyanobacteria in the freshwater crustacean Daphnia magna. Interclonal variation in tolerance to cyanobacteria disappears when Daphnia are made germ-free and inoculated with an identical microbial inoculum. Instead, variation in tolerance among recipient Daphnia mirrors that of the microbiota donors. Metagenetic analyses point to host genotype and external microbial source as important determinants of gut microbiota assembly, and reveal strong differences in gut microbiota composition between tolerant and susceptible genotypes. Together, these results show that both environmentally and host genotype-induced variations in gut microbiota structure mediate Daphnia tolerance to toxic cyanobacteria, pointing to the gut microbiota as a driver of adaptation and acclimatization to cyanobacterial harmful algal blooms in zooplankton.

Food availability affects the strength of mutualistic host-microbiota interactions in Daphnia magna.

The symbiotic gut microbial community is generally known to have a strong impact on the fitness of its host. Nevertheless, it is less clear how the impact of symbiotic interactions on the hosts' fitness varies according to environmental circumstances such as changes in the diet. This study aims to get a better understanding of host-microbiota interactions under different levels of food availability. We conducted experiments with the invertebrate, experimental model organism Daphnia magna and compared growth, survival and reproduction of conventionalized symbiotic Daphnia with germ-free individuals given varying quantities of food. Our experiments revealed that the relative importance of the microbiota for the hosts' fitness varied according to dietary conditions. The presence of the microbiota had strong positive effects on Daphnia when food was sufficient or abundant, but had weaker effects under food limitation. Our results indicate that the microbiota can be a potentially important factor in determining host responses to changes in dietary conditions. Characterization of the host-associated microbiota further showed that Aeromonas sp. was the most prevalent taxon in the digestive tract of Daphnia.