Both pathogen and host dynamically adapt pH responses along the intestinal tract during enteric bacterial infection.

Enteric pathogens navigate distinct regional microenvironments within the intestine that cue important adaptive behaviors. We investigated the response of Citrobacter rodentium, a model of human pathogenic Escherichia coli infection in mice, to regional gastrointestinal pH. We found that small intestinal pH (4.4-4.8) triggered virulence gene expression and altered cell morphology, supporting initial intestinal attachment, while higher pH, representative of C. rodentium's replicative niches further along the murine intestine, supported pathogen growth. Gastric pH, a key barrier to intestinal colonization, caused significant accumulation of intra-bacterial reactive oxygen species (ROS), inhibiting growth of C. rodentium and related human pathogens. Within-host adaptation increased gastric acid survival, which may be due to a robust acid tolerance response (ATR) induced at colonic pH. However, the intestinal environment changes throughout the course of infection. We found that murine gastric pH decreases postinfection, corresponding to increased serum gastrin levels and altered host expression of acid secretion-related genes. Similar responses following Salmonella infection may indicate a protective host response to limit further pathogen ingestion. Together, we highlight interlinked bacterial and host adaptive pH responses as an important component of host-pathogen coevolution.

Filling the gaps on root hair development under salt stress and phosphate starvation using current evidence coupled with a meta-analysis approach.

Population expansion is a global issue, especially for food production. Meanwhile, global climate change is damaging our soils, making it difficult for crops to thrive and lowering both production and quality. Poor nutrition and salinity stress affect plant growth and development. Although the impact of individual plant stresses has been studied for decades, the real stress scenario is more complex due to the exposure to multiple stresses at the same time. Here we investigate using existing evidence and a meta-analysis approach to determine molecular linkages between two contemporaneous abiotic stimuli, phosphate (Pi) deficiency and salinity, on a single plant cell model, the root hairs (RHs), which is the first plant cell exposed to them. Understanding how these two stresses work molecularly in RHs may help us build super-adaptable crops and sustainable agriculture in the face of global climate change.

Inference of annealed protein fitness landscapes with AnnealDCA.

The design of proteins with specific tasks is a major challenge in molecular biology with important diagnostic and therapeutic applications. High-throughput screening methods have been developed to systematically evaluate protein activity, but only a small fraction of possible protein variants can be tested using these techniques. Computational models that explore the sequence space in-silico to identify the fittest molecules for a given function are needed to overcome this limitation. In this article, we propose AnnealDCA, a machine-learning framework to learn the protein fitness landscape from sequencing data derived from a broad range of experiments that use selection and sequencing to quantify protein activity. We demonstrate the effectiveness of our method by applying it to antibody Rep-Seq data of immunized mice and screening experiments, assessing the quality of the fitness landscape reconstructions. Our method can be applied to several experimental cases where a population of protein variants undergoes various rounds of selection and sequencing, without relying on the computation of variants enrichment ratios, and thus can be used even in cases of disjoint sequence samples.

Inference and design of antibody specificity: From experiments to models and back.

Exquisite binding specificity is essential for many protein functions but is difficult to engineer. Many biotechnological or biomedical applications require the discrimination of very similar ligands, which poses the challenge of designing protein sequences with highly specific binding profiles. Experimental methods for generating specific binders rely on in vitro selection, which is limited in terms of library size and control over specificity profiles. Additional control was recently demonstrated through high-throughput sequencing and downstream computational analysis. Here we follow such an approach to demonstrate the design of specific antibodies beyond those probed experimentally. We do so in a context where very similar epitopes need to be discriminated, and where these epitopes cannot be experimentally dissociated from other epitopes present in the selection. Our approach involves the identification of different binding modes, each associated with a particular ligand against which the antibodies are either selected or not. Using data from phage display experiments, we show that the model successfully disentangles these modes, even when they are associated with chemically very similar ligands. Additionally, we demonstrate and validate experimentally the computational design of antibodies with customized specificity profiles, either with specific high affinity for a particular target ligand, or with cross-specificity for multiple target ligands. Overall, our results showcase the potential of leveraging a biophysical model learned from selections against multiple ligands to design proteins with tailored specificity, with applications to protein engineering extending beyond the design of antibodies.

Unsupervised modeling of mutational landscapes of adeno-associated viruses viability.

Adeno-associated viruses 2 (AAV2) are minute viruses renowned for their capacity to infect human cells and akin organisms. They have recently emerged as prominent candidates in the field of gene therapy, primarily attributed to their inherent non-pathogenic nature in humans and the safety associated with their manipulation. The efficacy of AAV2 as gene therapy vectors hinges on their ability to infiltrate host cells, a phenomenon reliant on their competence to construct a capsid capable of breaching the nucleus of the target cell. To enhance their infection potential, researchers have extensively scrutinized various combinatorial libraries by introducing mutations into the capsid, aiming to boost their effectiveness. The emergence of high-throughput experimental techniques, like deep mutational scanning (DMS), has made it feasible to experimentally assess the fitness of these libraries for their intended purpose. Notably, machine learning is starting to demonstrate its potential in addressing predictions within the mutational landscape from sequence data. In this context, we introduce a biophysically-inspired model designed to predict the viability of genetic variants in DMS experiments. This model is tailored to a specific segment of the CAP region within AAV2's capsid protein. To evaluate its effectiveness, we conduct model training with diverse datasets, each tailored to explore different aspects of the mutational landscape influenced by the selection process. Our assessment of the biophysical model centers on two primary objectives: (i) providing quantitative forecasts for the log-selectivity of variants and (ii) deploying it as a binary classifier to categorize sequences into viable and non-viable classes.

Is the time below 90% of SpO2 during sleep (T90%) a metric of good health? A longitudinal analysis of two cohorts.

BACKGROUND: Novel wireless-based technologies can easily record pulse oximetry at home. One of the main parameters that are recorded in sleep studies is the time under 90% of SpO2 (T90%) and the oxygen desaturation index 3% (ODI-3%). We assessed the association of T90% and/or ODI-3% in two different scenarios (a community-based study and a clinical setting) with all-cause mortality (primary outcome). METHODS: We included all individuals from the Sleep Heart Health Study (SHHS, community-based cohort) and Santiago Obstructive Sleep Apnea (SantOSA, clinical cohort) with complete data at baseline and follow-up. Two measures of hypoxemia (T90% and ODI-3%) were our primary exposures. The adjusted hazard ratios (HRs) per standard deviation (pSD) between T90% and incident all-cause mortality (primary outcome) were determined by adjusted Cox regression models. In the secondary analysis, to assess whether T90% varies across clinical factors, anthropometrics, abdominal obesity, metabolic rate, and SpO2, we conducted linear regression models. Incremental changes in R2 were conducted to test the hypothesis. RESULTS: A total of 4323 (56% male, median 64 years old, follow-up: 12 years, 23% events) and 1345 (77% male, median 55 years old, follow-up: 6 years, 11.6% events) patients were included in SHHS and SantOSA, respectively. Every 1 SD increase in T90% was associated with an adjusted HR of 1.18 [95% CI: 1.10-1.26] (p value < 0.001) in SHHS and HR 1.34 [95% CI: 1.04-1.71] (p value = 0.021) for all-cause mortality in SantOSA. Conversely, ODI-3% was not associated with worse outcomes. R2 explains 62% of the variability in T90%. The main contributors were baseline-mean change in SpO2, baseline SpO2, respiratory events, and age. CONCLUSION: The findings suggest that T90% may be an important marker of wellness in clinical and community-based scenarios. Although this nonspecific metric varies across the populations, ventilatory changes during sleep rather than other physiological or comorbidity variables explain their variability.

Expression and purification of active shikimate dehydrogenase from Plasmodium falciparum.

Plasmodium falciparum is known to cause severe malaria, current treatment consists in artemisinin-based combination therapy, but resistance can lead to treatment failure. Knowledge concerning P. falciparum essential proteins can be used for searching new antimalarials, among these a potential candidate is shikimate dehydrogenase (SDH), an enzyme part of the shikimate pathway which is responsible for producing endogenous aromatic amino acids. SDH from P. falciparum (PfSDH) is unexplored by the scientific community, therefore, this study aims to establish the first protocol for active PfSDH expression. Putative PfSDH nucleotide sequence was used to construct an optimized expression vector pET28a+PfSDH inserted in E. coli BL21(DE3). As a result, optimal expression conditions were acquired by varying IPTG and temperature through time. Western Blot analysis was applied to verify appropriate PfSDH expression, solubilization and purification started with lysis followed by two-steps IMAC purification. Enzyme activity was measured spectrophotometrically by NADPH oxidation, optimal PfSDH expression occur at 0.1 mM IPTG for 48 hours growing at 37 °C and shaking at 200 rpm, recombinant PfSDH obtained after purification was soluble, pure and its physiological catalysis was confirmed. Thus, this study describes the first protocol for heterologous expression of PfSDH in soluble and active form.

A Pro-Inflammatory Stimulus versus Extensive Passaging of DITNC1 Astrocyte Cultures as Models to Study Astrogliosis.

Astrogliosis is a process by which astrocytes, when exposed to inflammation, exhibit hypertrophy, motility, and elevated expression of reactivity markers such as Glial Fibrillar Acidic Protein, Vimentin, and Connexin43. Since 1999, our laboratory in Chile has been studying molecular signaling pathways associated with "gliosis" and has reported that reactive astrocytes upregulate Syndecan 4 and αVß3 Integrin, which are receptors for the neuronal glycoprotein Thy-1. Thy-1 engagement stimulates adhesion and migration of reactive astrocytes and induces neurons to retract neurites, thus hindering neuronal network repair. Reportedly, we have used DITNC1 astrocytes and neuron-like CAD cells to study signaling mechanisms activated by the Syndecan 4-αVß3 Integrin/Thy-1 interaction. Importantly, the sole overexpression of ß3 Integrin in non-reactive astrocytes turns them into reactive cells. In vitro, extensive passaging is a simile for "aging", and aged fibroblasts have shown ß3 Integrin upregulation. However, it is not known if astrocytes upregulate ß3 Integrin after successive cell passages. Here, we hypothesized that astrocytes undergoing long-term passaging increase ß3 Integrin expression levels and behave as reactive astrocytes without needing pro-inflammatory stimuli. We used DITNC1 cells with different passage numbers to study reactivity markers using immunoblots, immunofluorescence, and astrocyte adhesion/migration assays. We also evaluated ß3 Integrin levels by immunoblot and flow cytometry, as well as the neurotoxic effects of reactive astrocytes. Serial cell passaging mimicked the effects of inflammatory stimuli, inducing astrocyte reactivity. Indeed, in response to Thy-1, ß3 Integrin levels, as well as cell adhesion and migration, gradually increased with multiple passages. Importantly, these long-lived astrocytes expressed and secreted factors that inhibited neurite outgrowth and caused neuronal death, just like reactive astrocytes in culture. Therefore, we describe two DITNC1 cell types: a non-reactive type that can be activated with Tumor Necrosis Factor (TNF) and another one that exhibits reactive astrocyte features even in the absence of TNF treatment. Our results emphasize the importance of passage numbers in cell behavior. Likewise, we compare the pro-inflammatory stimulus versus long-term in-plate passaging of cell cultures and introduce them as astrocyte models to study the reactivity process.

[Obstructive Sleep Apnea and Nocturnal Hypoxemia Increase the Cardiovascular Risk in Chilean]. / La apnea obstructiva del sueño y la hipoxemia nocturna aumentan el riesgo cardiovascular basal en población chilena.

Obstructive sleep apnea (OSA) and cardiovascular (CV) risk co-existence is frequent. However, the implications of novel metrics used in the diagnosis of OSA in patients with CV risk are scarce in the Hispanic/Latino population. AIM: To determine the association between the respiratory disturbance index (RDI) and the Time under 90% of SpO2 (CT90%) with CV risk using the predictive model of Framingham 2008. In addition, we analyzed the diagnostic performance of the baseline CV risk model, adjusted for RDI, CT90%, and their combination to predict CV mortality. in patients with clinical suspicion of AOS. METHODS: Single-center prospective cohort study, including 1560 subjects. All patients underwent a clinical evaluation for OSA, blood pressure, and anthropometric variables. To determine the association of the indices of interest with CV risk, a linear multivariate regression was performed between the RDI or CT90% score. All analyses were performed using R software (R-project), and a p-value < 0.05 was considered statistically significant. RESULTS: RDI and CT90% showed significant differences for CV (p-value= <0.001). In addition, a percentage increase was demonstrated in each quartile of the RDI and CT90% (p-value= <0.001). CONCLUSIONS: The RDI and CT90% showed a significant and incremental association with the CV risk of the cohort. However, predictive analyses of CV mortality using the RDI and CT90% were not significant.

[Understanding food insecurity in rural families: A case study in Pueblo Nuevo, Cordoba, Colombia]. / Comprendiendo la inseguridad alimentaria en familias rurales: un estudio de caso en Pueblo Nuevo (Córdoba, Colombia).

The aim was to determine the possible association between food insecurity and the sociodemographic conditions of families in the rural area of Pueblo Nuevo, Córdoba, Colombia. It was a cross-sectional study using surveys to collect sociodemographic and food insecurity data in a rural area of Pueblo Nuevo, Córdoba, Colombia in which 391 families were surveyed to obtain relevant information. The Latin American and Caribbean Food Security Scale (ELCSA) survey was applied to evaluate the food security of the families. A descriptive analysis of qualitative and quantitative variables, and polyserial correlations to establish relationships between food insecurity and sociodemographic variables was held. Only 5 families (1%) showed adequate food security (AFS), while 235 families were in the severe food insecurity (SFI) category. Positive correlations were observed between types of food security and educational level (P<0.023), family income (P<0.001), and household size (P=0.002). A high prevalence of food insecurity was evident in the studied families, influenced by household size, lack of income, and low educational levels.

"Super-Spreaders" and Person-to-Person Transmission of Andes Virus in Argentina.

BACKGROUND: From November 2018 through February 2019, person-to-person transmission of Andes virus (ANDV) hantavirus pulmonary syndrome occurred in Chubut Province, Argentina, and resulted in 34 confirmed infections and 11 deaths. Understanding the genomic, epidemiologic, and clinical characteristics of person-to-person transmission of ANDV is crucial to designing effective interventions. METHODS: Clinical and epidemiologic information was obtained by means of patient report and from public health centers. Serologic testing, contact-tracing, and next-generation sequencing were used to identify ANDV infection as the cause of this outbreak of hantavirus pulmonary syndrome and to reconstruct person-to-person transmission events. RESULTS: After a single introduction of ANDV from a rodent reservoir into the human population, transmission was driven by 3 symptomatic persons who attended crowded social events. After 18 cases were confirmed, public health officials enforced isolation of persons with confirmed cases and self-quarantine of possible contacts; these measures most likely curtailed further spread. The median reproductive number (the number of secondary cases caused by an infected person during the infectious period) was 2.12 before the control measures were enforced and decreased to 0.96 after the measures were implemented. Full genome sequencing of the ANDV strain involved in this outbreak was performed with specimens from 27 patients and showed that the strain that was present (Epuyén/18-19) was similar to the causative strain (Epilink/96) in the first known person-to-person transmission of hantavirus pulmonary syndrome caused by ANDV, which occurred in El Bolsón, Argentina, in 1996. Clinical investigations involving patients with ANDV hantavirus pulmonary syndrome in this outbreak revealed that patients with a high viral load and liver injury were more likely than other patients to spread infection. Disease severity, genomic diversity, age, and time spent in the hospital had no clear association with secondary transmission. CONCLUSIONS: Among patients with ANDV hantavirus pulmonary syndrome, high viral titers in combination with attendance at massive social gatherings or extensive contact among persons were associated with a higher likelihood of transmission. (Funded by the Ministerio de Salud y Desarrollo Social de la Nación Argentina and others.).

A centronuclear myopathy-causing mutation in dynamin-2 disrupts neuronal morphology and excitatory synaptic transmission in a murine model of the disease.

AIMS: Dynamin-2 is a large GTPase, a member of the dynamin superfamily that regulates membrane remodelling and cytoskeleton dynamics. Mutations in the dynamin-2 gene (DNM2) cause autosomal dominant centronuclear myopathy (CNM), a congenital neuromuscular disorder characterised by progressive weakness and atrophy of the skeletal muscles. Cognitive defects have been reported in some DNM2-linked CNM patients suggesting that these mutations can also affect the central nervous system (CNS). Here we studied how a dynamin-2 CNM-causing mutation influences the CNS function. METHODS: Heterozygous mice harbouring the p.R465W mutation in the dynamin-2 gene (HTZ), the most common causing autosomal dominant CNM, were used as disease model. We evaluated dendritic arborisation and spine density in hippocampal cultured neurons, analysed excitatory synaptic transmission by electrophysiological field recordings in hippocampal slices, and evaluated cognitive function by performing behavioural tests. RESULTS: HTZ hippocampal neurons exhibited reduced dendritic arborisation and lower spine density than WT neurons, which was reversed by transfecting an interference RNA against the dynamin-2 mutant allele. Additionally, HTZ mice showed defective hippocampal excitatory synaptic transmission and reduced recognition memory compared to the WT condition. CONCLUSION: Our findings suggest that the dynamin-2 p.R465W mutation perturbs the synaptic and cognitive function in a CNM mouse model and support the idea that this GTPase plays a key role in regulating neuronal morphology and excitatory synaptic transmission in the hippocampus.

The Orphan GPCR Receptor, GPR88, Interacts with Nuclear Protein Partners in the Cerebral Cortex.

GPR88 is an orphan G-protein-coupled receptor (GPCR) highly expressed in striatal medium spiny neurons (MSN), also found in cortical neurons at low level. In MSN, GPR88 has a canonical GPCR plasma membrane/cytoplasmic expression, whereas in cortical neurons, we previously reported an atypical intranuclear localization. Molecular size analysis suggests that GPR88, expressed in plasma membrane of MSN or in nuclear compartment of cortical neurons, corresponds to the full-length protein. By transfection of cortical neurons, we showed that GPR88 fluorescent chimeras exhibit a nuclear localization. This localization is contingent on the third intracytoplasmic loop and C-terminus domains, even though these domains do not contain any known nuclear localization signals (NLS). Using yeast two-hybrid screening with these domains, we identified the nuclear proteins ATRX, TOP2B, and BAZ2B, all involved in chromatin remodeling, as potential protein partners of GPR88. We also validated the interaction of GPR88 with these nuclear proteins by proximity ligation assay on cortical neurons in culture and coimmunoprecipitation experiments on cortical extracts from GPR88 wild-type (WT) and knockout (KO) mice. The identification of GPR88 subcellular partners may provide novel functional insights for nonclassical modes of GPCR action that could be relevant in the maturating process of neocortical neurons.

MRI findings of primary intracranial sarcomas in children.

BACKGROUND: Primary intracranial sarcoma is a very rare high-grade tumor. Scant reports exist on this malignancy in children, which limit the information about its imaging characteristics. OBJECTIVE: We aimed to describe the main characteristics of primary intracranial sarcoma on MRI. MATERIALS AND METHODS: In this cross-sectional descriptive observational study, we reviewed 18 patients (aged 1-18 years) with primary intracranial sarcomas diagnosed between 2015 and 2021. RESULTS: The main findings were contrast enhancement (100%), diffusion restriction (78%), hemorrhage (89%), meningeal extension (67%), necrosis (67%), and supratentorial location (72%). CONCLUSION: Primary intracranial sarcoma are typically supratentorial in location. MRI findings of primary intracranial sarcoma are similar to other intracranial malignancies.

N-Sulfonyl-1,2,3,4-tetrahydroisoquinoline Derivatives: Synthesis, Antimicrobial Evaluations, and Theoretical Insights.

Microbial contamination remains a significant economic challenge in the food industry, emphasizing the need for innovative antimicrobial solutions. In this study, we synthesized N-sulfonyl-1,2,3,4-tetrahydroisoquinolines (NSTHIQ) derivatives using an environmentally friendly Preyssler heteropolyacid catalyst, obtaining moderate to high yields (35-91 %) under mild conditions. Two derivatives (5 and 6) exhibited significant antifungal properties against various fungal species, including Aspergillus spp, Penicillium spp, and Botrytis cinerea. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis revealed the absence of hepatic toxicity in all compounds, making derivatives 2, 3, 4, and 5 potential candidates for further development. However, derivatives 6 and 7 exhibited immunotoxicity. In support of our experimental findings, reactivity indices were computed using Density Functional Theory principles, deriving valuable insights into the chemical properties of these derivatives. This study underscores the potential of NSTHIQ compounds as potent antifungal agents, coupled with the importance of employing environmentally friendly catalysts in drug discovery.

Can We Predict Prostate Cancer Metastasis Based on Biomarkers? Where Are We Now?

The incidence of prostate cancer (PC) has risen annually. PC mortality is explained by the metastatic disease (mPC). There is an intermediate scenario in which patients have non-mPC but have initiated a metastatic cascade through epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict which patients will progress in the future to non-localized clinical disease or already have micrometastatic disease and, therefore, will clinically progress after primary treatment. Biomarkers for the prediction of mPC are still under development; there are few studies and not much evidence of their usefulness. This review is focused on tissue-based genomic biomarkers (TBGB) for the prediction of metastatic disease. We develop four main research questions that we attempt to answer according to the current evidence. Why is it important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are the current prostate cancer treatments? The importance of predicting metastasis is fundamental given that, once metastasis is diagnosed, quality of life (QoL) and survival drop dramatically. There is still a need and space for more cost-effective TBGB tests that predict mPC disease.

Dynamics of a cross-superdiffusive SIRS model with delay effects in transmission and treatment.

We investigate the dynamics of a SIRS epidemiological model taking into account cross-superdiffusion and delays in transmission, Beddington-DeAngelis incidence rate and Holling type II treatment. The superdiffusion is induced by inter-country and inter-urban exchange. The linear stability analysis for the steady-state solutions is performed, and the basic reproductive number is calculated. The sensitivity analysis of the basic reproductive number is presented, and we show that some parameters strongly influence the dynamics of the system. A bifurcation analysis to determine the direction and stability of the model is carried out using the normal form and center manifold theorem. The results reveal a proportionality between the transmission delay and the diffusion rate. The numerical results show the formation of patterns in the model, and their epidemiological implications are discussed.

The Effect of On-Site Potentials on Supratransmission in One-Dimensional Hamiltonian Lattices.

We investigated a class of one-dimensional (1D) Hamiltonian N-particle lattices whose binary interactions are quadratic and/or quartic in the potential. We also included on-site potential terms, frequently considered in connection with localization phenomena, in this class. Applying a sinusoidal perturbation at one end of the lattice and an absorbing boundary on the other, we studied the phenomenon of supratransmission and its dependence on two ranges of interactions, 0<α<∞ and 0<ß<∞, as the effect of the on-site potential terms of the Hamiltonian varied. In previous works, we studied the critical amplitude As(α,Ω) at which supratransmission occurs, for one range parameter α, and showed that there was a sharp threshold above which energy was transmitted in the form of large-amplitude nonlinear modes, as long as the driving frequency Ω lay in the forbidden band-gap of the system. In the absence of on-site potentials, it is known that As(α,Ω) increases monotonically the longer the range of interactions is (i.e., as α⟶0). However, when on-site potential terms are taken into account, As(α,Ω) reaches a maximum at a low value of α that depends on Ω, below which supratransmission thresholds decrease sharply to lower values. In this work, we studied this phenomenon further, as the contribution of the on-site potential terms varied, and we explored in detail their effect on the supratransmission thresholds.

Unsupervised Inference of Protein Fitness Landscape from Deep Mutational Scan.

The recent technological advances underlying the screening of large combinatorial libraries in high-throughput mutational scans deepen our understanding of adaptive protein evolution and boost its applications in protein design. Nevertheless, the large number of possible genotypes requires suitable computational methods for data analysis, the prediction of mutational effects, and the generation of optimized sequences. We describe a computational method that, trained on sequencing samples from multiple rounds of a screening experiment, provides a model of the genotype-fitness relationship. We tested the method on five large-scale mutational scans, yielding accurate predictions of the mutational effects on fitness. The inferred fitness landscape is robust to experimental and sampling noise and exhibits high generalization power in terms of broader sequence space exploration and higher fitness variant predictions. We investigate the role of epistasis and show that the inferred model provides structural information about the 3D contacts in the molecular fold.

Serotype-based evaluation of an optogenetic construct in rat cortical astrocytes.

Optogenetics is a modern technique which has been recently expanded to non-neuronal cell types, e.g., astrocytes, and involves targeted gene delivery of light-sensitive ion channels like Channelrhodopsin-2 (ChR2). Optogenetic regulation of astrocytic activity can be used for therapeutic intervention of several neurological disorders. Astrocytic gene delivery, viz adeno-associated viral (AAV) vectors, have proven to be robust, time-, and cost-efficient contrary to the generation of transgenic animal models. When transducing astrocytes with an AAV vector, it is imperative to perform a serotype evaluation of the AAV vector due to variability in serotype transduction efficiency depending on species, target region and construct length. Rats have been a very successful animal model for studying a variety of brain disorders, from which ChR2-based intervention of astrocytes will benefit. However, the most efficient AAV capsid serotype targeting astrocytes for ChR2 expression in the in vivo rat brain cortex has not been characterized. To address this, we have evaluated AAV serotypes 1, 5, and 8 of the vector AAV-GFAP-hChR2(H134)-mCherry targeting astrocytes in the rat brain neocortex. Results show that serotype 8 exhibits promising transduction patterns, as it has demonstrated the highest tangential and radial viral spread in the rat brain. Our research will facilitate translational research for future applications of optogenetics involving the transduction of rat brain cortical astrocytes.