Improved production of Taxol® precursors in S. cerevisiae using combinatorial in silico design and metabolic engineering.

BACKGROUND: Integrated metabolic engineering approaches that combine system and synthetic biology tools enable the efficient design of microbial cell factories for synthesizing high-value products. In this study, we utilized in silico design algorithms on the yeast genome-scale model to predict genomic modifications that could enhance the production of early-step Taxol® in engineered Saccharomyces cerevisiae cells. RESULTS: Using constraint-based reconstruction and analysis (COBRA) methods, we narrowed down the solution set of genomic modification candidates. We screened 17 genomic modifications, including nine gene deletions and eight gene overexpressions, through wet-lab studies to determine their impact on taxadiene production, the first metabolite in the Taxol® biosynthetic pathway. Under different cultivation conditions, most single genomic modifications resulted in increased taxadiene production. The strain named KM32, which contained four overexpressed genes (ILV2, TRR1, ADE13, and ECM31) involved in branched-chain amino acid biosynthesis, the thioredoxin system, de novo purine synthesis, and the pantothenate pathway, respectively, exhibited the best performance. KM32 achieved a 50% increase in taxadiene production, reaching 215 mg/L. Furthermore, KM32 produced the highest reported yields of taxa-4(20),11-dien-5α-ol (T5α-ol) at 43.65 mg/L and taxa-4(20),11-dien-5-α-yl acetate (T5αAc) at 26.2 mg/L among early-step Taxol® metabolites in S. cerevisiae. CONCLUSIONS: This study highlights the effectiveness of computational and integrated approaches in identifying promising genomic modifications that can enhance the performance of yeast cell factories. By employing in silico design algorithms and wet-lab screening, we successfully improved taxadiene production in engineered S. cerevisiae strains. The best-performing strain, KM32, achieved substantial increases in taxadiene as well as production of T5α-ol and T5αAc. These findings emphasize the importance of using systematic and integrated strategies to develop efficient yeast cell factories, providing potential implications for the industrial production of high-value isoprenoids like Taxol®.

Phonological and Semantic Fluency in Alzheimer's Disease: A Systematic Review and Meta-Analysis.

BACKGROUND: Semantic and Phonological fluency (SF and PF) are routinely evaluated in patients with Alzheimer's disease (AD). There are disagreements in the literature regarding which fluency task is more affected while developing AD. Most studies focus on SF assessment, given its connection with the temporoparietal amnesic system. PF is less reported, it is related to working memory, which is also impaired in probable and diagnosed AD. Differentiating between performance on these tasks might be informative in early AD diagnosis, providing an accurate linguistic profile. OBJECTIVE: Compare SF and PF performance in healthy volunteers, volunteers with probable AD, and patients with AD diagnosis, considering the heterogeneity of age, gender, and educational level variables. METHODS: A total of 8 studies were included for meta-analysis, reaching a sample size of 1,270 individuals (568 patients diagnosed with AD, 340 with probable AD diagnosis, and 362 healthy volunteers). RESULTS: The three groups consistently performed better on SF than PF. When progressing to a diagnosis of AD, we observed a significant difference in SF and PF performance across our 3 groups of interest (p = 0.04). The age variable explained a proportion of this difference in task performance across the groups, and as age increases, both tasks equally worsen. CONCLUSION: The performance of SF and PF might play a differential role in early AD diagnosis. These tasks rely on partially different neural bases of language processing. They are thus worth exploring independently in diagnosing normal aging and its transition to pathological stages, including probable and diagnosed AD.

First metagenomic analysis of the Andean condor (Vultur gryphus) gut microbiome reveals microbial diversity and wide resistome.

Background: The Andean condor (Vultur gryphus) is the largest scavenger in South America. This predatory bird plays a crucial role in their ecological niche by removing carcasses. We report the first metagenomic analysis of the Andean condor gut microbiome. Methods: This work analyzed shotgun metagenomics data from a mixture of fifteen captive Chilean Andean condors. To filter eukaryote contamination, we employed BWA-MEM v0.7. Taxonomy assignment was performed using Kraken2 and MetaPhlAn v2.0 and all filtered reads were assembled using IDBA-UD v1.1.3. The two most abundant species were used to perform a genome reference-guided assembly using MetaCompass. Finally, we performed a gene prediction using Prodigal and each gene predicted was functionally annotated. InterproScan v5.31-70.0 was additionally used to detect homology based on protein domains and KEGG mapper software for reconstructing metabolic pathways. Results: Our results demonstrate concordance with the other gut microbiome data from New World vultures. In the Andean condor, Firmicutes was the most abundant phylum present, with Clostridium perfringens, a potentially pathogenic bacterium for other animals, as dominating species in the gut microbiome. We assembled all reads corresponding to the top two species found in the condor gut microbiome, finding between 94% to 98% of completeness for Clostridium perfringens and Plesiomonas shigelloides, respectively. Our work highlights the ability of the Andean condor to act as an environmental reservoir and potential vector for critical priority pathogens which contain relevant genetic elements. Among these genetic elements, we found 71 antimicrobial resistance genes and 1,786 virulence factors that we associated with several adaptation processes.

Allostatic-Interoceptive Overload in Frontotemporal Dementia.

BACKGROUND: The predictive coding theory of allostatic-interoceptive load states that brain networks mediating autonomic regulation and interoceptive-exteroceptive balance regulate the internal milieu to anticipate future needs and environmental demands. These functions seem to be distinctly compromised in behavioral variant frontotemporal dementia (bvFTD), including alterations of the allostatic-interoceptive network (AIN). Here, we hypothesize that bvFTD is typified by an allostatic-interoceptive overload. METHODS: We assessed resting-state heartbeat evoked potential (rsHEP) modulation as well as its behavioral and multimodal neuroimaging correlates in patients with bvFTD relative to healthy control subjects and patients with Alzheimer's disease (N = 94). We measured 1) resting-state electroencephalography (to assess the rsHEP, prompted by visceral inputs and modulated by internal body sensing), 2) associations between rsHEP and its neural generators (source location), 3) cognitive disturbances (cognitive state, executive functions, facial emotion recognition), 4) brain atrophy, and 5) resting-state functional magnetic resonance imaging functional connectivity (AIN vs. control networks). RESULTS: Relative to healthy control subjects and patients with Alzheimer's disease, patients with bvFTD presented more negative rsHEP amplitudes with sources in critical hubs of the AIN (insula, amygdala, somatosensory cortex, hippocampus, anterior cingulate cortex). This exacerbated rsHEP modulation selectively predicted the patients' cognitive profile (including cognitive decline, executive dysfunction, and emotional impairments). In addition, increased rsHEP modulation in bvFTD was associated with decreased brain volume and connectivity of the AIN. Machine learning results confirmed AIN specificity in predicting the bvFTD group. CONCLUSIONS: Altogether, these results suggest that bvFTD may be characterized by an allostatic-interoceptive overload manifested in ongoing electrophysiological markers, brain atrophy, functional networks, and cognition.

Ocular Microbiome in a Group of Clinically Healthy Horses.

The ocular microbiome in horses is poorly described compared to other species, and most of the information available in the literature is based on traditional techniques, which has limited the depth of the knowledge on the subject. The objective of this study was to characterize and predict the metabolic pathways of the ocular microbiome of a group of healthy horses. Conjunctival swabs were obtained from both eyes of 14 horses, and DNA extraction was performed from the swabs, followed by next generation sequencing and bioinformatics analyses employing DADA2 and PICRUSt2. A total of 17 phyla were identified, of which Pseudomonadota (Proteobacteria) was the most abundant (59.88%), followed by Actinomycetota (Actinobacteria) (22.44%) and Bacteroidota (Bacteroidetes) (16.39%), totaling an average of 98.72% of the communities. Similarly, of the 278 genera identified, Massilia, Pedobacter, Pseudomonas, Sphingomonas, Suttonella and Verticia were present in more than 5% of the samples analyzed. Both Actinobacteria and Bacteroides showed great heterogeneity within the samples. The most abundant inferred metabolic functions were related to vital functions for bacteria such as aerobic respiration, amino acid, and lipid biosynthesis.

Isolation and Identification of Staphylococcus Species Obtained from Healthy Companion Animals and Humans.

The close contact between people and their pets has generated the exchange of skin microbiota, accompanied by bacteria that present resistance to antibiotics. Staphylococcus spp., opportunistic pathogens present in the skin and mucosa of mammals, have had their importance recognized in human and veterinary medicine. The objectives of this study were to identify Staphylococcus spp. present in isolates from the nostrils of healthy humans, dogs and cats as well as to determine their phenotype of resistance to methicillin. Strain identification was performed by MALDI-TOF mass spectrometry and antimicrobial susceptibility was determined using a disk diffusion assay for 12 antibiotics. Sixty humans (veterinary and technicians), sixty dogs and sixty cats were sampled; of them, 61.6%, 56.6% and 46.6%, respectively, carried Staphylococcus spp. in their nostrils, and only two people carried two different species of Staphylococcus in the only anatomical site sampled. A methicillin-resistant phenotype was present in 48.7% of the humans, 26.5% of the dogs and 57.1% of the cats, and sampled. These results demonstrate the presence of Staphylococcus spp. strains resistant to methicillin in personnel who work in contact with animals, as well as in dogs and cats that entered the same hospital or veterinary clinic, which alerts us to the potential transfer of these strains to or between people, dogs and/or cats.

Differences in the composition and predicted functions of the intestinal microbiome of obese and normal weight adult dogs.

Obesity is a multifactorial nutritional disorder highly prevalent in dogs, observed in developed and developing countries. It is estimated that over 40% of the canine population suffers from obesity, which manifests in an increased risk of chronic osteoarticular, metabolic, and cardiovascular diseases. The intestinal microbiome of obese animals shows increases in the abundance of certain members capable of extracting energy from complex polysaccharides. The objective of this study was to compare the composition and predicted function of the intestinal microbiome of Chilean obese and normal weight adult dogs. Twenty clinically healthy dogs were classified according to their body condition score (BCS) as obese (n = 10) or normal weight (n = 10). DNA was extracted from stool samples, followed by next-generation sequencing of the 16S rRNA V3-V4 region and bioinformatics analysis targeting microbiome composition and function. Significant differences were observed between these groups at the phylum level, with anincrease in Firmicutes and a decrease in Bacteroidetes in obese dogs. Microbiome compositions of these animals correlated with their BCS, and obese dogs showed enrichment in pathways related to transport, chemotaxis, and flagellar assembly. These results highlight the differences in the gut microbiome between normal weight and obese dogs and prompt further research to improve animal health by modulating the gut microbiome.

Characterization of microbial communities and predicted metabolic pathways in the uterus of healthy mares.

Background: Culture-independent techniques have made it possible to expand the knowledge about the composition of bacterial communities present in the healthy uterus and their role in health and disease, mainly in humans. However, in animals like mares, there is a dearth of information regarding this area. Aim: To narrow this knowledge gap, the objective of this study was to identify and characterize the composition and function of the uterine microbiome of a group of Chilean purebred mares (CPM), an equine breed with the oldest genealogical record in South America and an economical important reproductive industry. Methods: From uterine biopsy samples obtained during estrus, DNA extraction and targeted sequencing were performed to investigate the bacterial diversity and its probable metabolic function. Results: CPM biopsy samples were characterized by having a varied microbial composition, where the four most relatively abundant phyla were Proteobacteria (69.6%), Firmicutes (21.1%), Bacteroidetes (7.8%), and Actinobacteria (1.06%); which made up 99.6% of the total identified phyla. In contrast, Actinobacteria and Fusobacteria were the phyla not identified in all samples. Of a total of 59 genera identified across all samples, Staphylococcus was the most abundant genus with an average relative abundance of 18.88%, followed by Pseudomonas (17.9%), Escherichia/Shigella (10.42%), and Klebsiella (9.92%). Conclusion: These findings contribute to the knowledge of microbes' presence in the uterus, while future studies are required to demonstrate the role of these microorganisms in health and disease.

Assessment of Changes in the Oral Microbiome That Occur in Dogs with Periodontal Disease.

The oral microbiome in dogs is a complex community. Under some circumstances, it contributes to periodontal disease, a prevalent inflammatory disease characterized by a complex interaction between oral microbes and the immune system. Porphyromonas and Tannerella spp. are usually dominant in this disease. How the oral microbiome community is altered in periodontal disease, especially sub-dominant microbial populations is unclear. Moreover, how microbiome functions are altered in this disease has not been studied. In this study, we compared the composition and the predicted functions of the microbiome of the cavity of healthy dogs to those with from periodontal disease. The microbiome of both groups clustered separately, indicating important differences. Periodontal disease resulted in a significant increase in Bacteroidetes and reductions in Actinobacteria and Proteobacteria. Porphyromonas abundance increased 2.7 times in periodontal disease, accompanied by increases in Bacteroides and Fusobacterium. It was predicted that aerobic respiratory processes are decreased in periodontal disease. Enrichment in fermentative processes and anaerobic glycolysis were suggestive of an anaerobic environment, also characterized by higher lipopolysaccharide biosynthesis. This study contributes to a better understanding of how periodontal disease modifies the oral microbiome and makes a prediction of the metabolic pathways that contribute to the inflammatory process observed in periodontal disease.

Automated generation of context-specific gene regulatory networks with a weighted approach in Drosophila melanogaster.

The regulation of gene expression is a key factor in the development and maintenance of life in all organisms. Even so, little is known at whole genome scale for most genes and contexts. We propose a method, Tool for Weighted Epigenomic Networks in Drosophila melanogaster (Fly T-WEoN), to generate context-specific gene regulatory networks starting from a reference network that contains all known gene regulations in the fly. Unlikely regulations are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from the literature. Experimental data files can be generated with several standard procedures and used solely when and if available. Fly T-WEoN is available as a Cytoscape application that permits integration with other tools and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster. Fly T-WEoN together with its step-by-step guide is available at https://weon.readthedocs.io.

Atlas: automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages.

MOTIVATION: Cells are complex systems composed of hundreds of genes whose products interact to produce elaborated behaviors. To control such behaviors, cells rely on transcription factors to regulate gene expression, and gene regulatory networks (GRNs) are employed to describe and understand such behavior. However, GRNs are static models, and dynamic models are difficult to obtain due to their size, complexity, stochastic dynamics and interactions with other cell processes. RESULTS: We developed Atlas, a Python software that converts genome graphs and gene regulatory, interaction and metabolic networks into dynamic models. The software employs these biological networks to write rule-based models for the PySB framework. The underlying method is a divide-and-conquer strategy to obtain sub-models and combine them later into an ensemble model. To exemplify the utility of Atlas, we used networks of varying size and complexity of Escherichia coli and evaluated in silico modifications, such as gene knockouts and the insertion of promoters and terminators. Moreover, the methodology could be applied to the dynamic modeling of natural and synthetic networks of any bacteria. AVAILABILITY AND IMPLEMENTATION: Code, models and tutorials are available online (https://github.com/networkbiolab/atlas). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The impact of SARS-CoV-2 in dementia across Latin America: A call for an urgent regional plan and coordinated response.

The SARS-CoV-2 global pandemic will disproportionately impact countries with weak economies and vulnerable populations including people with dementia. Latin American and Caribbean countries (LACs) are burdened with unstable economic development, fragile health systems, massive economic disparities, and a high prevalence of dementia. Here, we underscore the selective impact of SARS-CoV-2 on dementia among LACs, the specific strain on health systems devoted to dementia, and the subsequent effect of increasing inequalities among those with dementia in the region. Implementation of best practices for mitigation and containment faces particularly steep challenges in LACs. Based upon our consideration of these issues, we urgently call for a coordinated action plan, including the development of inexpensive mass testing and multilevel regional coordination for dementia care and related actions. Brain health diplomacy should lead to a shared and escalated response across the region, coordinating leadership, and triangulation between governments and international multilateral networks.

Pleione: A tool for statistical and multi-objective calibration of Rule-based models.

Mathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures.

Short-term impact of sucralose consumption on the metabolic response and gut microbiome of healthy adults.

Sucralose is an artificial non-nutritive sweetener used in foods aimed to reduce sugar and energy intake. While thought to be inert, the impact of sucralose on metabolic control has shown to be the opposite. The gut microbiome has emerged as a factor shaping metabolic responses after sweetener consumption. We examined the short-term effect of sucralose consumption on glucose homeostasis and gut microbiome of healthy male volunteers. We performed a randomised, double-blind study in thirty-four subjects divided into two groups, one that was administered sucralose capsules (780 mg/d for 7 d; n 17) and a control group receiving placebo (n 17). Before and after the intervention, glycaemic and insulinaemic responses were assessed with a standard oral glucose load (75 g). Insulin resistance was determined using homeostasis model assessment of insulin resistance and Matsuda indexes. The gut microbiome was evaluated before and after the intervention by 16S rRNA sequencing. During the study, body weight remained constant in both groups. Glycaemic control and insulin resistance were not affected during the 7-d period. At the phylum level, gut microbiome was not modified in any group. We classified subjects according to their change in insulinaemia after the intervention, to compare the microbiome of responders and non-responders. Independent of consuming sucralose or placebo, individuals with a higher insulinaemic response after the intervention had lower Bacteroidetes and higher Firmicutes abundances. In conclusion, consumption of high doses of sucralose for 7 d does not alter glycaemic control, insulin resistance, or gut microbiome in healthy individuals. However, it highlights the need to address individual responses to sucralose.

Rule-Based Models and Applications in Biology.

Complex systems are governed by dynamic processes whose underlying causal rules are difficult to unravel. However, chemical reactions, molecular interactions, and many other complex systems can be usually represented as concentrations or quantities that vary over time, which provides a framework to study these dynamic relationships. An increasing number of tools use these quantifications to simulate dynamically complex systems to better understand their underlying processes. The application of such methods covers several research areas from biology and chemistry to ecology and even social sciences.In the following chapter, we introduce the concept of rule-based simulations based on the Stochastic Simulation Algorithm (SSA) as well as other mathematical methods such as Ordinary Differential Equations (ODE) models to describe agent-based systems. Besides, we describe the mathematical framework behind Kappa (κ), a rule-based language for the modeling of complex systems, and some extensions for spaßtial models implemented in PISKaS (Parallel Implementation of a Spatial Kappa Simulator). To facilitate the understanding of these methods, we include examples of how these models can be used to describe population dynamics in a simple predator-prey ecosystem or to simulate circadian rhythm changes.

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems.

Anatomic study of the distance between the lower margin of the mandible and the marginal mandibular branch of the facial nerve: a systematic review / Estudio anatómico de la distancia entre el margen mandibular y la rama marginal mandibular del nervio facial: una revisión sistemática

The marginal mandibular branch of the facial nerve (MMB) has a significant variation in relation to the lower border of the mandible (LBM). That is why it is important to know its topographical description to prevent damage in submandibular surgical procedures. The objective of this study was to determine the distance between the MMB and LBM based on descriptive studies carried out on human corpses and surgical patients. A systematic review of literature in MEDLINE, "Science Citation Index Expanded" of Web of Science (ISI) databases and manual search was performed. The articles with number of samples greater than or equal to 10 facial samples and recording of measurements between the MMB and the LBM or Gonion were selected. From the selected articles, the authors registered year of publication, country of origin, number of samples, sample type (fresh, embalmed body/fixed cadavers or surgical patient), distribution percentage of the MMB in relation to LBM, average and maximum distance between MMB and LBM or Gonion. The results were presented in tables with descriptive statistic. Seventeen articles describing measurements of the distance between MMB and the lower border of the mandible carried out in cadavers and patients were selected. In these articles a total of 1,408 samples were dissected. The maximum distance observed was 4.01 cm (mean±SD 1.64±0.92 cm, Min= 0.69; Max= 4.01). Several reports suggest that an incision 2 cm below the lower border of the mandible would be enough to avoid damage of the MMB. However, according to the maximal distances registered, such an incision might involve risk for the MMB. For this reason, we propose that the MMB of facial nerve should be at least 4 cm below the lower border of the mandible.

La rama mandibular marginal del nervio facial (RMM) posee variaciones significativas en su relación con el margen inferior de la mandíbula (MIM), siendo importante su descripción topográfica para evitar su daño en procedimientos quirúrgicos submandibulares. El objetivo fue determinar la distancia RMM y MIM observadas en humanos. Se realizó una revisión sistemática de la literatura en las bases de datos MEDLINE, "Science Citation Index Expanded" de Web of Science (ISI) y una búsqueda manual. Se seleccionaron artículos con análisis de 10 o más muestras y que registraran la distancia entre el RMM y el MIM o Gonion. Se registró autor, países de origen, condición de la muestra, número de muestras, distancias promedio y máximas registradas. Los resultados se analizaron mediante estadística descriptiva y presentada en tablas. Se seleccionaron 17 artículos con mediciones de las distancias entre el RMM y MIM tanto en cadáveres como pacientes. En total, 1,408 muestras fueron disecadas. La distancia máxima registrada fue de 4.01 cm (promedio±DE 1.64±0.92 cm, Min= 0,69; Max= 4,01). Diversos reportes sugieren que una incisión a 2 cm bajo el margen inferior de la mandíbula sería suficiente para evitar el daño al RMM. Sin embargo, con las distancias máximas observadas dicha incisión podría generar un daño. Por lo tanto, esta revisión sugiere la presencia del RMM a lo menos a 4 cm bajo el margen inferior de la mandíbula.

Shared and differential traits in the accessory olfactory bulb of caviomorph rodents with particular reference to the semiaquatic capybara.

The vomeronasal system is crucial for social and sexual communication in mammals. Two populations of vomeronasal sensory neurons, each expressing Gαi2 or Gαo proteins, send projections to glomeruli of the rostral or caudal accessory olfactory bulb, rAOB and cAOB, respectively. In rodents, the Gαi2- and Gαo-expressing vomeronasal pathways have shown differential responses to small/volatile vs. large/non-volatile semiochemicals, respectively. Moreover, early gene expression suggests predominant activation of rAOB and cAOB neurons in sexual vs. aggressive contexts, respectively. We recently described the AOB of Octodon degus, a semiarid-inhabiting diurnal caviomorph. Their AOB has a cell indentation between subdomains and the rAOB is twice the size of the cAOB. Moreover, their AOB receives innervation from the lateral aspect, contrasting with the medial innervation of all other mammals examined to date. Aiming to relate AOB anatomy with lifestyle, we performed a morphometric study on the AOB of the capybara, a semiaquatic caviomorph whose lifestyle differs remarkably from that of O. degus. Capybaras mate in water and scent-mark their surroundings with oily deposits, mostly for male-male communication. We found that, similar to O. degus, the AOB of capybaras shows a lateral innervation of the vomeronasal nerve, a cell indentation between subdomains and heterogeneous subdomains, but in contrast to O. degus the caudal portion is larger than the rostral one. We also observed that four other caviomorph species present a lateral AOB innervation and a cell indentation between AOB subdomains, suggesting that those traits could represent apomorphies of the group. We propose that although some AOB traits may be phylogenetically conserved in caviomorphs, ecological specializations may play an important role in shaping the AOB.