Rapid Microbial Profiling through Multimodal Biosensors for Transversal Analysis.

The intricate interactions between host and microbial communities hold significant implications for biology and medicine. However, traditional microbial profiling methods face limitations in processing time, measurement of absolute abundance, detection of low biomass, discrimination between live and dead cells, and functional analysis. This study introduces a rapid multimodal microbial characterization platform, Multimodal Biosensors for Transversal Analysis (MBioTA), for capturing the taxonomy, viability, and functional genes of the microbiota. The platform incorporates single cell biosensors, scalable microwell arrays, and automated image processing for rapid transversal analysis in as few as 2 h. The multimodal biosensors simultaneously characterize the taxon, viability, and functional gene expression of individual cells. By automating the image processing workflow, the single cell analysis techniques enable the quantification of bacteria with sensitivity down to 0.0075%, showcasing its capability in detecting low biomass samples. We illustrate the applicability of the MBioTA platform through the transversal analysis of the gut microbiota composition, viability, and functionality in a familial Alzheimer's disease mouse model. The effectiveness, rapid turnaround, and scalability of the MBioTA platform will facilitate its application from basic research to clinical diagnostics, potentially revolutionizing our understanding and management of diseases associated with microbe-host interactions.

Exploring memory-related network via dorsal hippocampus suppression.

Memory is a complex brain process that requires coordinated activities in a large-scale brain network. However, the relationship between coordinated brain network activities and memory-related behavior is not well understood. In this study, we investigated this issue by suppressing the activity in the dorsal hippocampus (dHP) using chemogenetics and measuring the corresponding changes in brain-wide resting-state functional connectivity (RSFC) and memory behavior in awake rats. We identified an extended brain network contributing to the performance in a spatial-memory related task. Our results were cross-validated using two different chemogenetic actuators, clozapine (CLZ) and clozapine-N-oxide (CNO). This study provides a brain network interpretation of memory performance, indicating that memory is associated with coordinated brain-wide neural activities. Significance Statement: Successful memory processes require coordinated activity in a large-scale brain network, extending beyond a few key, well-known brain regions like the hippocampus. However, the specific brain regions involved and how they orchestrate their activity that is pertinent to memory processing remain unclear. Our study, using a chemogenetics-rsfMRI- behavior approach in awake rats, elucidates a comprehensive framework of the extended memory-associated network. This knowledge offers a broader interpretation of memory processes, enhancing our understanding of the neural mechanisms behind memory function, particularly from a network perspective.

Sequential deactivation across the thalamus-hippocampus-mPFC pathway during loss of consciousness.

How consciousness is lost in states such as sleep or anesthesia remains a mystery. To gain insight into this phenomenon, we conducted concurrent recordings of electrophysiology signals in the anterior cingulate cortex and whole-brain functional magnetic resonance imaging (fMRI) in rats exposed to graded propofol, undergoing the transition from consciousness to unconsciousness. Our results reveal that upon the loss of consciousness (LOC), as indicated by the loss of righting reflex, there is a sharp increase in low-frequency power of the electrophysiological signal. Additionally, simultaneously measured fMRI signals exhibit a cascade of deactivation across a pathway including the hippocampus, thalamus, and medial prefrontal cortex (mPFC) surrounding the moment of LOC, followed by a broader increase in brain activity across the cortex during sustained unconsciousness. Furthermore, sliding window analysis demonstrates a temporary increase in synchrony of fMRI signals across the hippocampus-thalamus-mPFC pathway preceding LOC. These data suggest that LOC might be triggered by sequential activities in the hippocampus, thalamus and mPFC, while wide-spread activity increases in other cortical regions commonly observed during anesthesia-induced unconsciousness might be a consequence, rather than a cause of LOC. Taken together, our study identifies a cascade of neural events unfolding as the brain transitions into unconsciousness, offering critical insight into the systems-level neural mechanisms underpinning LOC.

Cytokine expression patterns predict suppression of vulnerable neural circuits in a mouse model of Alzheimer's disease.

Alzheimer's disease is a neurodegenerative disorder characterized by progressive amyloid plaque accumulation, tau tangle formation, neuroimmune dysregulation, synapse an neuron loss, and changes in neural circuit activation that lead to cognitive decline and dementia. Early molecular and cellular disease-instigating events occur 20 or more years prior to presentation of symptoms, making them difficult to study, and for many years amyloid-ß, the aggregating peptide seeding amyloid plaques, was thought to be the toxic factor responsible for cognitive deficit. However, strategies targeting amyloid-ß aggregation and deposition have largely failed to produce safe and effective therapies, and amyloid plaque levels poorly correlate with cognitive outcomes. However, a role still exists for amyloid-ß in the variation in an individual's immune response to early, soluble forms of aggregates, and the downstream consequences of this immune response for aberrant cellular behaviors and creation of a detrimental tissue environment that harms neuron health and causes changes in neural circuit activation. Here, we perform functional magnetic resonance imaging of awake, unanesthetized Alzheimer's disease mice to map changes in functional connectivity over the course of disease progression, in comparison to wild-type littermates. In these same individual animals, we spatiotemporally profile the immune milieu by measuring cytokines, chemokines, and growth factors across various brain regions and over the course of disease progression from pre-pathology through established cognitive deficit. We identify specific signatures of immune activation predicting hyperactivity followed by suppression of intra- and then inter-regional functional connectivity in multiple disease-relevant brain regions, following the pattern of spread of amyloid pathology.

Amyloid-ß Pathology-Specific Cytokine Secretion Suppresses Neuronal Mitochondrial Metabolism.

Introduction: Neuroinflammation and metabolic dysfunction are early alterations in Alzheimer's disease (AD) brain that are thought to contribute to disease onset and progression. Glial activation due to protein deposition results in cytokine secretion and shifts in brain metabolism, which have been observed in AD patients. However, the mechanism by which this immunometabolic feedback loop can injure neurons and cause neurodegeneration remains unclear. Methods: We used Luminex XMAP technology to quantify hippocampal cytokine concentrations in the 5xFAD mouse model of AD at milestone timepoints in disease development. We used partial least squares regression to build cytokine signatures predictive of disease progression, as compared to healthy aging in wild-type littermates. We applied the disease-defining cytokine signature to wild-type primary neuron cultures and measured downstream changes in gene expression using the NanoString nCounter system and mitochondrial function using the Seahorse Extracellular Flux live-cell analyzer. Results: We identified a pattern of up-regulated IFNγ, IP-10/CXCL10, and IL-9 as predictive of advanced disease. When healthy neurons were exposed to these cytokines in proportions found in diseased brain, gene expression of mitochondrial electron transport chain complexes, including ATP synthase, was suppressed. In live cells, basal and maximal mitochondrial respiration were impaired following cytokine stimulation. Conclusions: We identify a pattern of cytokine secretion predictive of progressing amyloid-ß pathology in the 5xFAD mouse model of AD that reduces expression of mitochondrial electron transport complexes and impairs mitochondrial respiration in healthy neurons. We establish a mechanistic link between disease-specific immune cues and impaired neuronal metabolism, potentially causing neuronal vulnerability and susceptibility to degeneration in AD. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-023-00782-y.

Alzheimer's disease-specific cytokine secretion suppresses neuronal mitochondrial metabolism.

Introduction: Neuroinflammation and metabolic dysfunction are early alterations in Alzheimer's disease brain that are thought to contribute to disease onset and progression. Glial activation due to protein deposition results in cytokine secretion and shifts in brain metabolism, which have been observed in Alzheimer's disease patients. However, the mechanism by which this immunometabolic feedback loop can injure neurons and cause neurodegeneration remains unclear. Methods: We used Luminex XMAP technology to quantify hippocampal cytokine concentrations in the 5xFAD mouse model of Alzheimer's disease at milestone timepoints in disease development. We used partial least squares regression to build cytokine signatures predictive of disease progression, as compared to healthy aging in wild-type littermates. We applied the disease-defining cytokine signature to wild-type primary neuron cultures and measured downstream changes in gene expression using the NanoString nCounter system and mitochondrial function using the Seahorse Extracellular Flux live-cell analyzer. Results: We identified a pattern of up-regulated IFNγ, IP-10, and IL-9 as predictive of advanced disease. When healthy neurons were exposed to these cytokines in proportions found in diseased brain, gene expression of mitochondrial electron transport chain complexes, including ATP synthase, was suppressed. In live cells, basal and maximal mitochondrial respiration were impaired following cytokine stimulation. Conclusions: An Alzheimer's disease-specific pattern of cytokine secretion reduces expression of mitochondrial electron transport complexes and impairs mitochondrial respiration in healthy neurons. We establish a mechanistic link between disease-specific immune cues and impaired neuronal metabolism, potentially causing neuronal vulnerability and susceptibility to degeneration in Alzheimer's disease.

Apolipoprotein E ε4 modulates astrocyte neuronal support functions in the presence of amyloid-ß.

Apolipoprotein E (APOE) is a lipid transporter produced predominantly by astrocytes in the brain. The ε4 variant of APOE (APOE4) is the strongest and most common genetic risk factor for Alzheimer's disease (AD). Although the molecular mechanisms of this increased risk are unclear, APOE4 is known to alter immune signaling and lipid and glucose metabolism. Astrocytes provide various forms of support to neurons, including regulating neuronal metabolism and immune responses through cytokine signaling. Changes in astrocyte function because of APOE4 may therefore decrease neuronal support, leaving neurons more vulnerable to stress and disease insults. To determine whether APOE4 alters astrocyte neuronal support functions, we measured glycolytic and oxidative metabolism of neurons treated with conditioned media from APOE4 or APOE3 (the common, risk-neutral variant) primary astrocyte cultures. We found that APOE4 neurons treated with conditioned media from resting APOE4 astrocytes had similar metabolism to APOE3 neurons treated with media from resting APOE3 astrocytes, but treatment with astrocytic conditioned media from astrocytes challenged with amyloid-ß (Aß), a key pathological protein in AD, caused APOE4 neurons to increase their basal mitochondrial and glycolytic metabolic rates more than APOE3 neurons. These changes were not because of differences in astrocytic lactate production or glucose utilization, but instead correlated with increased glycolytic ATP production and a lack of cytokine secretion in response to Aß. Additionally, we identified that astrocytic cytokine signatures could predict basal metabolism of neurons treated with the astrocytic conditioned media. Together, these findings suggest that in the presence of Aß, APOE4 astrocytes alter immune and metabolic functions that result in a compensatory increase in neuronal metabolic stress.

Predictive link between systemic metabolism and cytokine signatures in the brain of apolipoprotein E ε4 mice.

The ε4 variant of apolipoprotein E (APOE) is the strongest and most common genetic risk factor for Alzheimer's disease (AD). While the mechanism of conveyed risk is incompletely understood, promotion of inflammation, dysregulated metabolism, and protein misfolding and aggregation are contributors to accelerating disease. Here we determined the concurrent effects of systemic metabolic changes and brain inflammation in young (3-month-old) and aged (18-month-old) male and female mice carrying the APOE4 gene. Using functional metabolic assays alongside multivariate modeling of hippocampal cytokine levels, we found that brain cytokine signatures are predictive of systemic metabolic outcomes, independent of AD proteinopathies. Male and female mice each produce different cytokine signatures as they age and as their systemic metabolic phenotype declines, and these signatures are APOE genotype dependent. Ours is the first study to identify a quantitative and predictive link between systemic metabolism and specific pathological cytokine signatures in the brain. Our results highlight the effects of APOE4 beyond the brain and suggest the potential for bi-directional influence of risk factors in the brain and periphery.

Pathogen-specific antimicrobials engineered de novo through membrane-protein biomimicry.

Precision antimicrobials aim to kill pathogens without damaging commensal bacteria in the host, and thereby cure disease without antibiotic-associated dysbiosis. Here we report the de novo design of a synthetic host defence peptide that targets a specific pathogen by mimicking key molecular features of the pathogen's channel-forming membrane proteins. By exploiting physical and structural vulnerabilities within the pathogen's cellular envelope, we designed a peptide sequence that undergoes instructed tryptophan-zippered assembly within the mycolic acid-rich outer membrane of Mycobacterium tuberculosis to specifically kill the pathogen without collateral toxicity towards lung commensal bacteria or host tissue. These mycomembrane-templated assemblies elicit rapid mycobactericidal activity and enhance the potency of antibiotics by improving their otherwise poor diffusion across the rigid M. tuberculosis envelope with respect to agents that exploit transmembrane protein channels for antimycobacterial activity. This biomimetic strategy may aid the design of other narrow-spectrum antimicrobial peptides.

Volumetric optical mapping in early embryonic hearts using light-sheet microscopy.

Optical mapping (OM) of electrical activity using voltage-sensitive fluorescent dyes is a powerful tool for the investigation of embryonic cardiac electrophysiology. However, because conventional OM integrates the signal in depth and projects it to a two-dimensional plane, information acquired is incomplete and dependent upon the orientation of the sample. This complicates interpretation of data, especially when comparing one heart to another. To overcome this limitation, we present volumetric OM using light-sheet microscopy, which enables high-speed capture of optically sectioned slices. Voltage-sensitive fluorescence images from multiple planes across entire early embryonic quail hearts were acquired, and complete, orientation-independent, four-dimensional maps of transmembrane potential are demonstrated. Volumetric OM data were collected while using optical pacing to control the heart rate, paving the way for physiological measurements and precise manipulation of the heartbeat in the future.