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Freezing of gait (FoG), a paroxysmal gait disturbance commonly experienced by patients with Parkinson’s disease (PD), is characterized by sudden episodes of inability to generate effective forward stepping. Recent studies have shown an increase in beta frequency of local-field potentials in the basal-ganglia during FoG, however, comprehensive research on the synchronization between different brain locations and frequency bands in PD patients is scarce. Here, by developing tools based on network science and non-linear dynamics, we analyze synchronization networks of electroencephalography (EEG) brain waves of three PD patient groups with different FoG severity. We find higher EEG amplitude synchronization (stronger network links) between different brain locations as PD and FoG severity increase. These results are consistent across frequency bands (theta, alpha, beta, gamma) and independent of the specific motor task (walking, still standing, hand tapping) suggesting that an increase in severity of PD and FoG is associated with stronger EEG networks over a broad range of brain frequencies. This observation of a direct relationship of PD/FoG severity with overall EEG synchronization together with our proposed EEG synchronization network approach may be used for evaluating FoG propensity and help to gain further insight into PD and the pathophysiology leading to FoG., Asher et al analyzed synchronization networks of electroencephalography brain waves from three Parkinson’s disease (PD) patient groups with different freezing of gait (FoG) severity using tools based on network science and non-linear dynamics. Their findings suggest that there is a potential relationship between PD/FoG severity and overall EEG synchronization and their approach could be used to help gain further insight into the pathophysiology leading to FoG.

The recent recognition of the importance of the microbiome to the host’s health and well-being, has yielded efforts to develop therapies that aim to shift the microbiome from a disease-associated steady-state to a healthier one. Direct manipulation techniques of the species’ assemblage are currently available, e.g., using probiotics or narrow-spectrum antibiotics to introduce or eliminate specific taxa. However, predicting the species’ abundances at the new steady-state remains a challenge, mainly due to the difficulties of deciphering the delicate underlying network of ecological interactions or constructing a predictive model for such complex ecosystem. Here, we propose a model-free method to predict the species’ abundances at the new steady state based on their presence/absence configuration by utilizing a multi-dimensional k-nearest-neighbors (kNN) regression algorithm. By analyzing data from numeric simulations of ecological dynamics, we show that our predictions, which consider the presence/absence of all species holistically, outperform both the null model that uses the statistics of each species independently and a predictive neural network model. We analyze real metagenomic data of human-associated microbial communities and found that by relying on a small number of ‘neighboring’ samples, i.e., samples with similar species assemblage, the kNN predicts the species abundance better than the whole-cohort average. By studying both real metagenomic and simulated data, we show that the predictability of our method is tightly related to the dissimilarity-overlap relationship of the training data. Our results demonstrate how model-free methods can prove useful in predicting microbial communities and may facilitate the development of microbial-based therapies.

The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, is spreading rapidly throughout the world, causing many deaths and severe economic damage. It is believed that hot and humid conditions do not favor the novel coronavirus, yet this is still under debate due to many uncertainties associated with the COVID-19 data. Here we propose surrogate data tests to examine the preference of this virus to spread under different climate conditions. We find, by mainly studying the relative number of COVID-19 deaths, that the disease is significantly (above the 95% confidence level) more common when the temperature is ∼10 °C, the relative humidity is ∼60%, the specific humidity is ∼5 g kg−1, and the ultraviolet radiation is less than ∼50 kJ m−2 (per hour). We also find, but less significantly, that the relative number of COVID-19 deaths is high when the wind is weak and low when the wind is strong. The results are supported based on global and regional data, spanning the time period from January to December 2020. The COVID-19 data includes the daily reported new cases and the daily deaths; for both, the population size is either taken into account or ignored.

Modularity is a key organizing principle in real-world large-scale complex networks. Many real-world networks exhibit modular structures such as transportation infrastructures, communication networks and social media. Having the knowledge of the shortest paths length distribution (DSPL) between random pairs of nodes in such networks is important for understanding many processes, including diffusion or flow. Here, we provide analytical methods which are in good agreement with simulations on large scale networks with an extreme modular structure. By extreme modular, we mean that two modules or communities may be connected by maximum one link. As a result of the modular structure of the network, we obtain a distribution showing many peaks that represent the number of modules a typical shortest path is passing through. We present theory and results for the case where inter-links are weighted, as well as cases in which the inter-links are spread randomly across nodes in the community or limited to a specific set of nodes., 12 pages, 13 figures

Summary: Tight regulation of neuronal transport allows for cargo binding and release at specific cellular locations. The mechanisms by which motor proteins are loaded on vesicles and how cargoes are captured at appropriate sites remain unclear. To better understand how KIF1A-driven dense core vesicle (DCV) transport is regulated, we identified the KIF1A interactome and focused on three binding partners, the calcium binding protein calmodulin (CaM) and two synaptic scaffolding proteins: liprin-α and TANC2. We showed that calcium, acting via CaM, enhances KIF1A binding to DCVs and increases vesicle motility. In contrast, liprin-α and TANC2 are not part of the KIF1A-cargo complex but capture DCVs at dendritic spines. Furthermore, we found that specific TANC2 mutations—reported in patients with different neuropsychiatric disorders—abolish the interaction with KIF1A. We propose a model in which Ca2+/CaM regulates cargo binding and liprin-α and TANC2 recruit KIF1A-transported vesicles. : Stucchi et al. show that KIF1A-dependent transport is regulated by CaM, liprin-α, and TANC2. KIF1A binding to DCVs is controlled by a Ca2+/CaM molecular mechanism, and KIF1A-driven DCVs are recruited in dendritic spines by the PSD scaffolds liprin-α and TANC2. Keywords: neuron, transport, dendritic spines, synapse, KIF1A, scaffold, calmodulin, calcium, TANC2, liprin-α

A family of membrane-associated proteins related to yeast Lag1p and mammalian TRAM has been identified. The family includes the protein product of CLN8, a gene mutated in progressive epilepsy with mental retardation. Mouse CLN8 is also mutated in the mnd/mnd mouse, a model for neuronal ceroid lipofuscinoses. The identification of these homologues has potential implications for our understanding of ceramide synthesis, lipid regulation and protein translocation in the endoplasmic reticulum.

Variation in gene expression has been held responsible for the functional and morphological specialization of tissues. The tissue specificity of genes is known to correlate positively with gene evolution rates. We show here, using large data sets, that when a gene is expressed highly in a small number of tissues, its protein is more likely to be secreted and more likely to be mutated in genetic diseases with Mendelian inheritance. We find that secreted proteins are evolving at faster rates than nonsecreted proteins, and that their evolutionary rates are highly correlated with tissue specificity. However, the impact of secretion on evolutionary rates is countered by tissue-specific constraints that have been held constant over the past 75 million years. We find that disease genes are underrepresented among intracellular and slowly evolving housekeeping genes. These findings illuminate major selective pressures that have shaped the gene repertoires expressed in different mammalian tissues.

Human disease genes differ significantly from their rodent orthologs with respect to their overall levels of conservation and their rates of evolutionary change. Rodent orthologs of human trinucleotide repeat-expansion disease genes were also found to contain substantially fewer such repeats., Background Model organisms have contributed substantially to our understanding of the etiology of human disease as well as having assisted with the development of new treatment modalities. The availability of the human, mouse and, most recently, the rat genome sequences now permit the comprehensive investigation of the rodent orthologs of genes associated with human disease. Here, we investigate whether human disease genes differ significantly from their rodent orthologs with respect to their overall levels of conservation and their rates of evolutionary change. Results Human disease genes are unevenly distributed among human chromosomes and are highly represented (99.5%) among human-rodent ortholog sets. Differences are revealed in evolutionary conservation and selection between different categories of human disease genes. Although selection appears not to have greatly discriminated between disease and non-disease genes, synonymous substitution rates are significantly higher for disease genes. In neurological and malformation syndrome disease systems, associated genes have evolved slowly whereas genes of the immune, hematological and pulmonary disease systems have changed more rapidly. Amino-acid substitutions associated with human inherited disease occur at sites that are more highly conserved than the average; nevertheless, 15 substituting amino acids associated with human disease were identified as wild-type amino acids in the rat. Rodent orthologs of human trinucleotide repeat-expansion disease genes were found to contain substantially fewer of such repeats. Six human genes that share the same characteristics as triplet repeat-expansion disease-associated genes were identified; although four of these genes are expressed in the brain, none is currently known to be associated with disease. Conclusions Most human disease genes have been retained in rodent genomes. Synonymous nucleotide substitutions occur at a higher rate in disease genes, a finding that may reflect increased mutation rates in the chromosomal regions in which disease genes are found. Rodent orthologs associated with neurological function exhibit the greatest evolutionary conservation; this suggests that rodent models of human neurological disease are likely to most faithfully represent human disease processes. However, with regard to neurological triplet repeat expansion-associated human disease genes, the contraction, relative to human, of rodent trinucleotide repeats suggests that rodent loci may not achieve a 'critical repeat threshold' necessary to undergo spontaneous pathological repeat expansions. The identification of six genes in this study that have multiple characteristics associated with repeat expansion-disease genes raises the possibility that not all human loci capable of facilitating neurological disease by repeat expansion have as yet been identified.

The laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality 'draft' covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineage-independent evolutionary events such as expansion of gene families, orthology relations and protein evolution.

The extensive similarities between the genomes of human and model organisms are the foundation of much of modern biology, with model organism experimentation permitting valuable insights into biological function and the aetiology of human disease. In contrast, differences among genomes have received less attention. Yet these can be expected to govern the physiological and morphological distinctions apparent among species, especially if such differences are the result of evolutionary adaptation. A recent comparison of the draft sequences of mouse and human genomes has shed light on the selective forces that have predominated in their recent evolutionary histories. In particular, mouse-specific clusters of homologues associated with roles in reproduction, immunity and host defence appear to be under diversifying positive selective pressure, as indicated by high ratios of non-synonymous to synonymous substitution rates. These clusters are also frequently punctuated by homologous pseudogenes. They thus have experienced numerous gene death, as well as gene birth, events. These regions appear, therefore, to have borne the brunt of adaptive evolution that underlies physiological and behavioural innovation in mice. We predict that the availability of numerous animal genomes will give rise to a new field of genome zoology in which differences in animal physiology and ethology are illuminated by the study of genomic sequence variations.

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.