Highly dynamic evolution of the chemosensory system driven by gene gain and loss across subterranean beetles.

Chemical cues in subterranean habitats differ highly from those on the surface due to the contrasting environmental conditions, such as absolute darkness, high humidity or food scarcity. Subterranean animals underwent changes to their sensory systems to facilitate the perception of essential stimuli for underground lifestyles. Despite representing unique systems to understand biological adaptation, the genomic basis of chemosensation across cave-dwelling species remains unexplored from a macroevolutionary perspective. Here, we explore the evolution of chemoreception in three beetle tribes that underwent at least six independent transitions to the underground, through a phylogenomics spyglass. Our findings suggest that the chemosensory gene repertoire varies dramatically between species. Overall, no parallel changes in the net rate of evolution of chemosensory gene families were detected prior, during, or after the habitat shift among subterranean lineages. Contrarily, we found evidence of lineage-specific changes within surface and subterranean lineages. However, our results reveal key duplications and losses shared between some of the lineages transitioning to the underground, including the loss of sugar receptors and gene duplications of the highly conserved ionotropic receptors IR25a and IR8a, involved in thermal and humidity sensing among other olfactory roles in insects. These duplications were detected both in independent subterranean lineages and their surface relatives, suggesting parallel evolution of these genes across lineages giving rise to cave-dwelling species. Overall, our results shed light on the genomic basis of chemoreception in subterranean beetles and contribute to our understanding of the genomic underpinnings of adaptation to the subterranean lifestyle at a macroevolutionary scale.

Evaluating a large language model's ability to solve programming exercises from an introductory bioinformatics course.

Computer programming is a fundamental tool for life scientists, allowing them to carry out essential research tasks. However, despite various educational efforts, learning to write code can be a challenging endeavor for students and researchers in life-sciences disciplines. Recent advances in artificial intelligence have made it possible to translate human-language prompts to functional code, raising questions about whether these technologies can aid (or replace) life scientists' efforts to write code. Using 184 programming exercises from an introductory-bioinformatics course, we evaluated the extent to which one such tool-OpenAI's ChatGPT-could successfully complete programming tasks. ChatGPT solved 139 (75.5%) of the exercises on its first attempt. For the remaining exercises, we provided natural-language feedback to the model, prompting it to try different approaches. Within 7 or fewer attempts, ChatGPT solved 179 (97.3%) of the exercises. These findings have implications for life-sciences education and research. Instructors may need to adapt their pedagogical approaches and assessment techniques to account for these new capabilities that are available to the general public. For some programming tasks, researchers may be able to work in collaboration with machine-learning models to produce functional code.

Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk.

Research studies based on tractography have revealed a prominent reduction of asymmetry in some key white-matter tracts in schizophrenia (SCZ). However, we know little about the influence of common genetic risk factors for SCZ on the efficiency of routing on structural brain networks (SBNs). Here, we use a novel recall-by-genotype approach, where we sample young adults from a population-based cohort (ALSPAC:N genotyped = 8,365) based on their burden of common SCZ risk alleles as defined by polygenic risk score (PRS). We compared 181 individuals at extremes of low (N = 91) or high (N = 90) SCZ-PRS under a robust diffusion MRI-based graph theoretical SBN framework. We applied a semi-metric analysis revealing higher SMR values for the high SCZ-PRS group compared with the low SCZ-PRS group in the left hemisphere. Furthermore, a hemispheric asymmetry index showed a higher leftward preponderance of indirect connections for the high SCZ-PRS group compared with the low SCZ-PRS group (PFDR < 0.05). These findings might indicate less efficient structural connectivity in the higher genetic risk group. This is the first study in a population-based sample that reveals differences in the efficiency of SBNs associated with common genetic risk variants for SCZ.

Short Sequence Aligner Benchmarking for Chromatin Research.

Much of today's molecular science revolves around next-generation sequencing. Frequently, the first step in analyzing such data is aligning sequencing reads to a reference genome. This step is often taken for granted, but any analysis downstream of the alignment will be affected by the aligner's ability to correctly map sequences. In most cases, for research into chromatin structure and nucleosome positioning, ATAC-seq, ChIP-seq, and MNase-seq experiments use short read lengths. How well aligners manage these reads is critical. Most aligner programs will output mapped reads and unmapped reads. However, from a biological point of view, reads will fall into one of three categories: correctly mapped, incorrectly mapped, and unmapped. While increased sequencing depth can often compensate for unmapped reads, incorrectly and correctly mapped reads appear algorithmically identical but can produce biologically significant alterations in the results. For this reason, we are benchmarking various alignment programs to determine their propensity to incorrectly map short reads. As short-read alignment is an important step in ATAC-seq, ChIP-seq, and MNase-seq experiments, caution should be taken in mapping reads to ensure that the most accurate conclusions can be made from the data generated. Our analysis is intended to help investigators new to the field pick the alignment program best suited for their experimental conditions. In general, the aligners we tested performed well. BWA, Bowtie2, and Chromap were all exceptionally accurate, and we recommend using them. Furthermore, we show that longer read lengths do in fact lead to more accurate mappings.

Parallel decay of vision genes in subterranean water beetles.

In the framework of neutral theory of molecular evolution, genes specific to the development and function of eyes in subterranean animals living in permanent darkness are expected to evolve by relaxed selection, ultimately becoming pseudogenes. However, definitive empirical evidence for the role of neutral processes in the loss of vision over evolutionary time remains controversial. In previous studies, we characterized an assemblage of independently-evolved water beetle (Dytiscidae) species from a subterranean archipelago in Western Australia, where parallel vision and eye loss have occurred. Using a combination of transcriptomics and exon capture, we present evidence of parallel coding sequence decay, resulting from the accumulation of frameshift mutations and premature stop codons, in eight phototransduction genes (arrestins, opsins, ninaC and transient receptor potential channel genes) in 32 subterranean species in contrast to surface species, where these genes have open reading frames. Our results provide strong evidence to support neutral evolutionary processes as a major contributing factor to the loss of phototransduction genes in subterranean animals, with the ultimate fate being the irreversible loss of a light detection system.

Advances in glycopeptide enrichment methods for the analysis of protein glycosylation over the past decade.

Advances in bioanalytical technology have accelerated the analysis of complex protein glycosylation, which is beneficial to understand glycosylation in drug discovery and disease diagnosis. Due to its biological uniqueness in the course of disease occurrence and development, disease-specific glycosylation requires quantitative characterization of protein glycosylation. We provide a comprehensive review of recent advances in glycosylation analysis, including workflows for glycoprotein digestion, glycopeptide separation and enrichment, and mass spectrometry sequencing. We specifically focus on different strategies for glycopeptide enrichment through physical interaction, chemical oxidation, or metabolic labeling of intact glycopeptides. Recent advances and challenges of O-glycosylation analysis are presented, and the development of improved enrichment methods combining different proteases to analyze O-glycosylation is also proposed.

Sequential Ensemble-Decision Aliquot Ranking Isolation and Fluorescence In Situ Hybridization Identification of Rare Cells from Blood by Using Concentrated Peripheral Blood Mononuclear Cells.

Isolation and analysis of circulating rare cells is a promising approach for early detection of cancer and other diseases and for prenatal diagnosis. Isolation of rare cells is usually difficult due to their heterogeneity as well as their low abundance in peripheral blood. We previously reported a two-stage ensemble-decision aliquot ranking platform (S-eDAR) for isolating circulating tumor cells from whole blood with high throughput, high recovery rate (>90%), and good purity (>70%), allowing detection of low surface antigen-expressing cancer cells linked to metastasis. However, due to the scarcity of these cells, large sample volumes and large quantities of antibodies were required to isolate sufficient cells for downstream analysis. Here, we drastically increased the number of nucleated cells analyzed by first concentrating peripheral blood mononuclear cells (PBMCs) from whole blood by density gradient centrifugation. The S-eDAR platform was capable of isolating rare cells from concentrated PBMCs (108/mL, equivalent to processing ∼20 mL of whole blood in the 1 mL sample volume used by our instrument) at a high recovery rate (>85%). We then applied the S-eDAR platform for isolating rare fetal nucleated red blood cells (fNRBCs) from concentrated PBMCs spiked with umbilical cord blood cells and confirmed fNRBC recovery by immunostaining and fluorescence in situ hybridization, demonstrating the potential of the S-eDAR system for isolating rare fetal cells from maternal PBMCs to improve noninvasive prenatal diagnosis.

ExtRamp: a novel algorithm for extracting the ramp sequence based on the tRNA adaptation index or relative codon adaptiveness.

Different species, genes, and locations within genes use different codons to fine-tune gene expression. Within genes, the ramp sequence assists in ribosome spacing and decreases downstream collisions by incorporating slowly-translated codons at the beginning of a gene. Although previously reported as occurring in some species, no previous attempt at extracting the ramp sequence from specific genes has been published. We present ExtRamp, a software package that quickly extracts ramp sequences from any species using the tRNA adaptation index or relative codon adaptiveness. Different filters facilitate the analysis of codon efficiency and enable identification of genes with a ramp sequence. We validate the existence of a ramp sequence in most species by running ExtRamp on 229 742 339 genes across 23 428 species. We evaluate differences in reported ramp sequences when we use different parameters. Using the strictest ramp sequence cut-off, we show that across most taxonomic groups, ramp sequences are approximately 20-40 codons long and occur in about 10% of gene sequences. We also show that in Drosophila melanogaster as gene expression increases, a higher proportion of genes have ramp sequences. We provide a framework for performing this analysis on other species. ExtRamp is freely available at https://github.com/ridgelab/ExtRamp.

JustOrthologs: a fast, accurate and user-friendly ortholog identification algorithm.

MOTIVATION: Orthologous gene identification is fundamental to all aspects of biology. For example, ortholog identification between species can provide functional insights for genes of unknown function and is a necessary step in phylogenetic inference. Currently, most ortholog identification algorithms require all-versus-all BLAST comparisons, which are time-consuming and memory intensive. RESULTS: In contrast to existing approaches, JustOrthologs exploits the conservation of gene structure by using the lengths of coding sequence regions and dinucleotide percentages to identify orthologs. In comparison to OrthoMCL, OMA and OrthoFinder, JustOrthologs decreases ortholog identification runtime by more than 96% and achieves comparable precision and recall scores. The computational speedup allowed us to conduct pairwise comparisons of 1197 complete genomes (780 eukaryotes and 417 archaea). We confirmed gene annotations for 384 120 genes, grouped 1 675 415 genes in previously unreported ortholog groups, and identified 51 429 potentially mislabeled genes across 622 843 ortholog groups. AVAILABILITY AND IMPLEMENTATION: JustOrthologs is an open source collaborative software package available in the GitHub repository: https://github.com/ridgelab/JustOrthologs/. All test FASTA files used for comparisons are freely available at https://github.com/ridgelab/JustOrthologs/comparisonFastaFiles/. Reference genomes used in this work are available for download from the NCBI repository: ftp://ftp.ncbi.nih.gov/genomes/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Codon use and aversion is largely phylogenetically conserved across the tree of life.

Using parsimony, we analyzed codon usages across 12,337 species and 25,727 orthologous genes to rank specific genes and codons according to their phylogenetic signal. We examined each codon within each ortholog to determine the codon usage for each species. In total, 890,814 codons were parsimony informative. Next, we compared species that used a codon with species that did not use the codon. We assessed each codon's congruence with species relationships provided in the Open Tree of Life (OTL) and determined the statistical probability of observing these results by random chance. We determined that 25,771 codons had no parallelisms or reversals when mapped to the OTL. Codon usages from orthologous genes spanning many species were 1109× more likely to be congruent with species relationships in the OTL than would be expected by random chance. Using the OTL as a reference, we show that codon usage is phylogenetically conserved within orthologous genes in archaea, bacteria, plants, mammals, and other vertebrates. We also show how to use our provided framework to test different tree hypotheses by confirming the placement of turtles as sister taxa to archosaurs.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease.

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD). These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case-control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer's disease in seven independent case-control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer's disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer's disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer's disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-ß precursor protein (APP) and extracellular Aß42 and Aß40 (the 42- and 40-residue isoforms of the amyloid-ß peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aß42 and Aß40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

Isolating Rare Cells and Circulating Tumor Cells with High Purity by Sequential eDAR.

Isolation and analysis of circulating tumor cells (CTCs) from the blood of patients at risk of metastatic cancers is a promising approach to improving cancer treatment. However, CTC isolation is difficult due to low CTC abundance and heterogeneity. Previously, we reported an ensemble-decision aliquot ranking (eDAR) platform for the rare cell and CTC isolation with high throughput, greater than 90% recovery, and high sensitivity, allowing detection of low surface antigen-expressing cells linked to metastasis. Here we demonstrate a sequential eDAR platform capable of isolating rare cells from whole blood with high purity. This improvement in purity is achieved by using a sequential sorting and flow stretching design in which whole blood is sorted and fluid elements are stretched using herringbone features and the parabolic flow profile being sorted a second time. This platform can be used to collect single CTCs in a multiwell plate for downstream analysis.

Arabidopsis thaliana organelles mimic the T7 phage DNA replisome with specific interactions between Twinkle protein and DNA polymerases Pol1A and Pol1B.

BACKGROUND: Plant chloroplasts and mitochondria utilize nuclear encoded proteins to replicate their DNA. These proteins are purposely built for replication in the organelle environment and are distinct from those involved in replication of the nuclear genome. These organelle-localized proteins have ancestral roots in bacterial and bacteriophage genes, supporting the endosymbiotic theory of their origin. We examined the interactions between three of these proteins from Arabidopsis thaliana: a DNA helicase-primase similar to bacteriophage T7 gp4 protein and animal mitochondrial Twinkle, and two DNA polymerases, Pol1A and Pol1B. We used a three-pronged approach to analyze the interactions, including Yeast-two-hybrid analysis, Direct Coupling Analysis (DCA), and thermophoresis. RESULTS: Yeast-two-hybrid analysis reveals residues 120-295 of Twinkle as the minimal region that can still interact with Pol1A or Pol1B. This region is a part of the primase domain of the protein and slightly overlaps the zinc-finger and RNA polymerase subdomains located within. Additionally, we observed that Arabidopsis Twinkle interacts much more strongly with Pol1A versus Pol1B. Thermophoresis also confirms that the primase domain of Twinkle has higher binding affinity than any other region of the protein. Direct-Coupling-Analysis identified specific residues in Twinkle and the DNA polymerases critical to positive interaction between the two proteins. CONCLUSIONS: The interaction of Twinkle with Pol1A or Pol1B mimics the minimal DNA replisomes of T7 phage and those present in mammalian mitochondria. However, while T7 and mammals absolutely require their homolog of Twinkle DNA helicase-primase, Arabidopsis Twinkle mutants are seemingly unaffected by this loss. This implies that while Arabidopsis mitochondria mimic minimal replisomes from T7 and mammalian mitochondria, there is an extra level of redundancy specific to loss of Twinkle function.

Molecular epidemiology of carbapenem-resistance plasmids using publicly available sequences.

Carbapenem-resistant bacteria have quickly become a worldwide concern in nosocomial infections. Of the seven known carbapenemases, four have been shown to be particularly problematic: KPC, NDM, IMP, and VIM. To date, many local and species- or carbapenemase-specific epidemiological studies have been performed, which often focus on the organism itself. This report attempts to perform an inclusive (encompass both species and carbapenemase) epidemiologic study using publicly available plasmid sequences from NCBI. In this report, the gene content of these various plasmids has been characterized, replicon types of the plasmids identified, and the global spread and species promiscuity of the plasmids analyzed. Additionally, support to several groups targeting plasmid maintenance and transfer mechanisms to slow the spread of resistance plasmids is given.

Impact of opioid-induced constipation on healthcare resource utilization and costs for cancer pain patients receiving continuous opioid therapy.

PURPOSE: Opioid therapy is often associated with adverse effects, including opioid-induced constipation (OIC), in patients receiving opioids for cancer pain. This retrospective observational cohort study evaluated healthcare utilization and costs during the first year after initiating opioid therapy among cancer patients with (cohort 1) and without (cohort 2) constipation. METHODS: This study used administrative claims data from the HealthCore Integrated Research Environment between January 1, 2006, and April 30, 2014. Eligible patients included adults ≥ 18 years with a diagnosis of cancer who initiated continuous opioid therapy (≥ 30 days). Propensity scores were used to match patients with constipation in a 1:1 ratio to those without constipation. Generalized linear models were used to evaluate healthcare utilization and costs during the 12 months after initiating opioid therapy. RESULTS: After matching, 1369 patients were included in each cohort. Patients with constipation were more than twice as likely as those without constipation to have an all-cause inpatient hospitalization (odds ratio [95% confidence interval (CI)], 2.47 [2.11-2.90]), or pain-related hospitalization (2.15 [1.82-2.54]) during the 12 months after initiating therapy. Mean unadjusted overall healthcare costs during the first 12 months post-index were $21,629 (95% CI, $14,850-$29,018) higher for patients with constipation than for those without constipation. For patients with constipation, total mean (SD) constipation-related costs were $9196 ($26,896). CONCLUSIONS: These results suggest that OIC is associated with significantly increased healthcare and economic burden in cancer pain patients and that early and ongoing recognition and management of OIC are unmet needs in this population.

Impacts of chronic and increasing lipopolysaccharide exposure on production and reproductive parameters in lactating Holstein dairy cows.

Lipopolysaccharide (LPS) administration causes immunoactivation, which negatively affects production and fertility, but experimental exposure via an acute bolus is unlikely to resemble natural infections. Thus, the objectives were to characterize effects of chronic endotoxemia on production parameters and follicular development in estrous-synchronized lactating cows. Eleven Holstein cows (169 ± 20 d in milk; 681 ± 16 kg of body weight) were acclimated to their environmental surroundings for 3 d and then enrolled in 2 experimental periods (P). During P1 (3 d) cows consumed feed ad libitum and baseline samples were obtained. During P2 (7 d), cows were assigned to continuous infusion of either (1) saline-infused and pair-fed (CON-PF; 40 mL/h of saline i.v.; n = 5) or (2) LPS infused and ad libitum fed (LPS-AL; Escherichia coli O55:B5; 0.017, 0.020, 0.026, 0.036, 0.055, 0.088, and 0.148 µg/kg of body weight/h i.v. on d 1 to 7, respectively; n = 6). Controls were pair-fed to the LPS-AL group to eliminate confounding effects of dissimilar nutrient intake. Infusing LPS temporally caused mild hyperthermia on d 1 to 3 (+0.49°C) relative to baseline. Dry matter intake of LPS-AL cows decreased (28%) on d 1 of P2, then progressively returned to baseline. Relative to baseline, milk yield from LPS-AL cows was decreased on d 1 of P2 (12%). No treatment differences were observed in milk yield during P2. Follicular growth, dominant follicle size, serum progesterone (P4), and follicular P4 and 17ß-estradiol concentrations were similar between treatments. Serum 17ß-estradiol tended to increase (115%) and serum amyloid A and LPS-binding protein were increased (118 and 40%, respectively) in LPS-AL relative to CON-PF cows. Compared with CON-PF, neutrophils in LPS-AL cows were initially increased (45%), then gradually decreased. In contrast, monocytes were initially decreased (40%) and progressively increased with time in the LPS-AL cows. Hepatic mRNA abundance of cytochrome P450 family 2 subfamily C (CYP2C) or CYP3A was not affected by LPS, nor was there a treatment effect on toll-like receptor 4 or LBP; however, acyloxyacyl hydrolase and RELA subunit of nuclear factor kappa B tended to be increased in LPS-AL cows. These data suggest lactating dairy cows become tolerant to chronic and exponentially increasing LPS infusion in terms of production and reproductive parameters.

Kmer-SSR: a fast and exhaustive SSR search algorithm.

MOTIVATION: One of the main challenges with bioinformatics software is that the size and complexity of datasets necessitate trading speed for accuracy, or completeness. To combat this problem of computational complexity, a plethora of heuristic algorithms have arisen that report a 'good enough' solution to biological questions. However, in instances such as Simple Sequence Repeats (SSRs), a 'good enough' solution may not accurately portray results in population genetics, phylogenetics and forensics, which require accurate SSRs to calculate intra- and inter-species interactions. RESULTS: We present Kmer-SSR, which finds all SSRs faster than most heuristic SSR identification algorithms in a parallelized, easy-to-use manner. The exhaustive Kmer-SSR option has 100% precision and 100% recall and accurately identifies every SSR of any specified length. To identify more biologically pertinent SSRs, we also developed several filters that allow users to easily view a subset of SSRs based on user input. Kmer-SSR, coupled with the filter options, accurately and intuitively identifies SSRs quickly and in a more user-friendly manner than any other SSR identification algorithm. AVAILABILITY AND IMPLEMENTATION: The source code is freely available on GitHub at https://github.com/ridgelab/Kmer-SSR. CONTACT: perry.ridge@byu.edu.

A revised phylogeny of macropathine cave crickets (Orthoptera: Rhaphidophoridae) uncovers a paraphyletic Australian fauna.

Australian cave crickets are members of the subfamily Macropathinae (Orthoptera: Rhaphidophoridae). The subfamily is thought to have originated prior to the tectonic separation of the supercontinent Gondwana based on distributions of extant lineages and molecular phylogenetic evidence, although the Australian fauna have been underrepresented in previous studies. The current study augments existing multigene data (using 12S, 16S, and 28S rRNA genes) to investigate the placement of the Australian representatives within the Macropathinae and to assess divergence dates of select clades. Results suggest that the endemic Tasmanian genus Parvotettix is the sister lineage to the remaining members of the subfamily, an outcome that presents a paraphyletic Australian fauna in contrast to previous studies. All other Australian taxa represented in this study (Micropathus and Novotettix) emerged as a sister group to the New Zealand and South American macropathine lineages. Estimation of phylogenetic divergence ages among the aforementioned clades were calibrated using two methods, in absence of suitable fossil records: (i) tectonic events depicting the fragmentation of Gondwanan landmasses that invoke vicariant scenarios of present day geographic distributions; and (ii) molecular evolutionary rates. Geological calibrations place the median age of the most recent common ancestor of extant macropathines at ∼125 to ∼165 Ma, whereas analyses derived from molecular substitution rates suggest a considerably younger origin of ∼32 Ma. This phylogenetic study represents the most rigorous taxonomic sampling of the Australian cave cricket fauna to date and stresses the influence of lineage representation on biogeographic inference.

Assembly of 809 whole mitochondrial genomes with clinical, imaging, and fluid biomarker phenotyping.

INTRODUCTION: Mitochondrial genetics are an important but largely neglected area of research in Alzheimer's disease. A major impediment is the lack of data sets. METHODS: We used an innovative, rigorous approach, combining several existing tools with our own, to accurately assemble and call variants in 809 whole mitochondrial genomes. RESULTS: To help address this impediment, we prepared a data set that consists of 809 complete and annotated mitochondrial genomes with samples from the Alzheimer's Disease Neuroimaging Initiative. These whole mitochondrial genomes include rich phenotyping, such as clinical, fluid biomarker, and imaging data, all of which is available through the Alzheimer's Disease Neuroimaging Initiative website. Genomes are cleaned, annotated, and prepared for analysis. DISCUSSION: These data provide an important resource for investigating the impact of mitochondrial genetic variation on risk for Alzheimer's disease and other phenotypes that have been measured in the Alzheimer's Disease Neuroimaging Initiative samples.

Dysfunctional tubular endoplasmic reticulum constitutes a pathological feature of Alzheimer's disease.

Pathological features in Alzheimer's brains include mitochondrial dysfunction and dystrophic neurites (DNs) in areas surrounding amyloid plaques. Using a mouse model that overexpresses reticulon 3 (RTN3) and spontaneously develops age-dependent hippocampal DNs, here we report that DNs contain both RTN3 and REEPs, topologically similar proteins that can shape tubular endoplasmic reticulum (ER). Importantly, ultrastructural examinations of such DNs revealed gradual accumulation of tubular ER in axonal termini, and such abnormal tubular ER inclusion is found in areas surrounding amyloid plaques in biopsy samples from Alzheimer's disease (AD) brains. Functionally, abnormally clustered tubular ER induces enhanced mitochondrial fission in the early stages of DN formation and eventual mitochondrial degeneration at later stages. Furthermore, such DNs are abrogated when RTN3 is ablated in aging and AD mouse models. Hence, abnormally clustered tubular ER can be pathogenic in brain regions: disrupting mitochondrial integrity, inducing DNs formation and impairing cognitive function in AD and aging brains.