Non-random Sequence Research Articles

Synapsin condensation is governed by sequence-encoded molecular grammars.

Multiple biomolecular condensates coexist at the pre- and post- synapse to enable vesicle dynamics and controlled neurotransmitter release in the brain. In pre-synapses, intrinsically disordered regions (IDRs) of synaptic proteins are drivers of condensation that enable clustering of synaptic vesicles (SVs). Using computational analysis, we show that the IDRs of SV proteins feature evolutionarily conserved non-random compositional biases and sequence patterns. Synapsin-1 is essential for condensation of SVs, and its C-terminal IDR has been shown to be a key driver of condensation. Focusing on this IDR, we dissected the contributions of two conserved features namely the segregation of polar and proline residues along the linear sequence, and the compositional preference for arginine over lysine. Scrambling the blocks of polar and proline residues weakens the driving forces for forming micron-scale condensates. However, the extent of clustering in subsaturated solutions remains equivalent to that of the wild-type synapsin-1. In contrast, substituting arginine with lysine significantly weakens both the driving forces for condensation and the extent of clustering in subsaturated solutions. Co-expression of the scrambled variant of synapsin-1 with synaptophysin results in a gain-of-function phenotype in cells, whereas arginine to lysine substitutions eliminate condensation. We report an emergent consequence of synapsin-1 condensation, which is the generation of interphase pH gradients realized via differential partitioning of protons between coexisting phases. This pH gradient is likely to be directly relevant for vesicular ATPase functions and the loading of neurotransmitters. Our study highlights how conserved IDR grammars serve as drivers of synapsin-1 condensation.

Sequence-dependent and -independent information in a combined random energy model for protein folding and coding.

Random energy models (REMs) provide a simple description of the energy landscapes that guide protein folding and evolution. The requirement of a large energy gap between the native structure and unfolded conformations, considered necessary for cooperative, protein-like, folding behavior, indicates that proteins differ markedly from random heteropolymers. It has been suggested, therefore, that natural selection might have acted to choose nonrandom amino acid sequences satisfying this particular condition, implying that a large fraction of possible, unselected random sequences, would not fold to any structure. From an informational perspective, however, this scenario could indicate that protein structures, regarded as messages to be transmitted through a communication channel, would not be efficiently encoded in amino acid sequences, regarded as the communication channel for this transmission, since a large fraction of possible channel states would not be used. Here, we use a combined REM for conformations and sequences, with previously estimated parameters for natural proteins, to explore an alternative possibility in which the appropriate shape of the landscape results mainly from the deviation from randomness of possible native structures instead of sequences. We observe that this situation emerges naturally if the distribution of conformational energies happens to arise from two independent contributions corresponding to sequence-dependent and -independent terms. This construction is consistent with the hypothesis of a protein burial folding code, with native structures being determined by a modest amount of sequence-dependent atomic burial information with sequence-independent constraints imposed by unspecific hydrogen bond formation. More generally, an appropriate combination of sequence-dependent and -independent information accommodates the possibility of an efficient structural encoding with the main physical requirement for folding, providing possible insight not only on the folding process but also on several aspects sequence evolution such as neutral networks, conformational coverage, and de novo gene emergence.

Retraction: Effect of adjunctive vaginal progesterone after McDonald cerclage on the rate of second-trimester abortion insingleton pregnancy: A randomized controlled trial.

M. K. Ali, S. E. Ahmed, G. H. Sayed, E. Y. Badran, A. M. Abbas. (2020), Effect of adjunctive vaginal progesterone after McDonald cerclage on the rate of second-trimester abortion in singleton pregnancy: a randomized controlled trial. International Journal of Gynecology & Obstetrics, 149: 370-376. https://doi.org/10.1002/ijgo.13148 The above article, published online on 04 April 2020 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, the journal Editor-in-Chief, Professor Michael Geary, the International Federation of Gynecology and Obstetrics, and John Wiley and Sons Ltd. Concerns were raised regarding the integrity of the data for this study, and the authors were asked to provide the raw data for review by the journal. On evaluation of the available data by the journal's research integrity team, several inconsistencies were found within the dataset, including non-random sequences which call into question the validity of the data. Subsequently, the authors carried out a full review and reanalysis of the data and discovered a considerable number of transcription errors, indicating significant discrepancies from the conclusions reported in the study. As such, the data for this study cannot be considered reliable and the journal is issuing this retraction.

Multiple neuron clusters on Micro-Electrode Arrays as an in vitro model of brain network

Understanding the brain functioning is essential for governing brain processes with the aim of managing pathological network dysfunctions. Due to the morphological and biochemical complexity of the central nervous system, the development of general models with predictive power must start from in vitro brain network engineering. In the present work, we realized a micro-electrode array (MEA)-based in vitro brain network and studied its emerging dynamical properties. We obtained four-neuron-clusters (4N) assemblies by plating rat embryo cortical neurons on 60-electrode MEA with cross-shaped polymeric masks and compared the emerging dynamics with those of sister single networks (1N). Both 1N and 4N assemblies exhibited spontaneous electrical activity characterized by spiking and bursting signals up to global activation by means of network bursts. Data revealed distinct patterns of network activity with differences between 1 and 4N. Rhythmic network bursts and dominant initiator clusters suggested pacemaker activities in both assembly types, but the propagation of activation sequences was statistically influenced by the assembly topology. We proved that this rhythmic activity was ivabradine sensitive, suggesting the involvement of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and propagated across the real clusters of 4N, or corresponding virtual clusters of 1N, with dominant initiator clusters, and nonrandom cluster activation sequences. The occurrence of nonrandom series of identical activation sequences in 4N revealed processes possibly ascribable to neuroplasticity. Hence, our multi-network dissociated cortical assemblies suggest the relevance of pacemaker neurons as essential elements for generating brain network electrophysiological patterns; indeed, such evidence should be considered in the development of computational models for envisaging network behavior both in physiological and pathological conditions.

Connecting sequence features within the disordered C-terminal linker of B. subtilis FtsZ to functions and bacterial cell division.

Intrinsically disordered regions (IDRs) can function as autoregulators of folded enzymes to which they are tethered. One such example is the disordered C-terminal tail (CTT) of FtsZ, an essential GTPase in bacterial cell division. FtsZs feature a folded core and a CTT that encompasses a poorly conserved, disordered C-terminal linker (CTL) and a conserved 17-residues C-terminal peptide (CT17). Sites for GTPase activity of FtsZs are formed at the interface between GTP binding sites and T7 loops on cores of adjacent subunits within dimers. Here, we explore the molecular, evolutionary, and cellular bases for how autoregulatory functions of the CTT are realized in Bacillus subtilis FtsZ (Bs-FtsZ). Molecular simulations show statistically significant CTL-mediated contacts between the T7 loop and the CT17. Statistical coupling analysis of more than 1000 orthologs reveals clear covariation of the T7 loop and the CT17 with most of the core domain whereas the CTL is under independent selection. Furthermore, we also identify a conserved set of non-random sequence patterns within the CTLs, including linear clustering of polar and acidic residues, that modulate the interaction between the core and the CTT. To test how the non-random patterns of CTLs mediate CTT-core interactions and modulate FtsZ functionalities, we designed Bs-FtsZ variants by altering the patterning of oppositely charged residues within the CTL. Such alterations disrupt the core-CTT interactions, lead to anomalous assembly and inefficient GTP hydrolysis in vitro, and protein degradation, aberrant assembly, and disruption of cell division in vivo. Our findings suggest that viable CTLs in FtsZs are likely to be IDRs that encompass the non-random, functionally relevant sequence patterns that also preserve three-way covariation of the CT17, the T7 loop, and core domain.

How long are the vocal sequences a passerine bird can memorize? Common song sequences of Radde’s warbler males (Phylloscopus schwarzi) (Passeriformes, Aves)

In most passerine species, an individual bird sings multiple song types to be combined into non-random song sequences. Because of this non-randomness, stereotype sequences of several or even dozens of song types appear in the vocalization of some species. Passerine birds acquire songs through some learning process while imitating other individuals. Song sharing is well known in songbirds and is a consequence of the song learning. Apparently, above the song type level, transitions between song types may be also shared. However, we still do not know exactly, how long are those song sequencies a bird can memorize? We analyze song sequence sharing in Radde’s warbler. Each song of this species consists of a dozen of short notes and lasts 1 s. In many males, the identity of the next song type in a sequence can be predicted on the basis of the previous song type (linear syntax). We found that males can share (i.e. memorize) song sequences from no more than 5 song types. Individual repertoires included up to 40 song types. Therefore, the ability of memorizing song sequences are rather limited in Radde’s warbler, as shared song sequences were rather short in comparison with the total size of the repertoire.

Connecting sequence features within the disordered C-terminal linker of Bacillus subtilis FtsZ to functions and bacterial cell division

Intrinsically disordered regions (IDRs) can function as autoregulators of folded enzymes to which they are tethered. One example is the bacterial cell division protein FtsZ. This includes a folded core and a C-terminal tail (CTT) that encompasses a poorly conserved, disordered C-terminal linker (CTL) and a well-conserved 17-residue C-terminal peptide (CT17). Sites for GTPase activity of FtsZs are formed at the interface between GTP binding sites and T7 loops on cores of adjacent subunits within dimers. Here, we explore the basis of autoregulatory functions of the CTT in Bacillus subtilis FtsZ (Bs-FtsZ). Molecular simulations show that the CT17 of Bs-FtsZ makes statistically significant CTL-mediated contacts with the T7 loop. Statistical coupling analysis of more than 1,000 sequences from FtsZ orthologs reveals clear covariation of the T7 loop and the CT17 with most of the core domain, whereas the CTL is under independent selection. Despite this, we discover the conservation of nonrandom sequence patterns within CTLs across orthologs. To test how the nonrandom patterns of CTLs mediate CTT-core interactions and modulate FtsZ functionalities, we designed Bs-FtsZ variants by altering the patterning of oppositely charged residues within the CTL. Such alterations disrupt the core-CTT interactions, lead to anomalous assembly and inefficient GTP hydrolysis invitro and protein degradation, aberrant assembly, and disruption of cell division invivo. Our findings suggest that viable CTLs in FtsZs are likely to be IDRs that encompass nonrandom, functionally relevant sequence patterns that also preserve three-way covariation of the CT17, the T7 loop, and core domain.

Automated prediction of site and sequence of protein modification with ATRP initiators.

One of the most straightforward and commonly used chemical modifications of proteins is to react surface amino groups (lysine residues) with activated esters. This chemistry has been used to generate protein-polymer conjugates, many of which are now approved therapeutics. Similar conjugates have also been generated by reacting activated ester atom transfer polymerization initiators with lysine residues to create biomacromolecular initiators for polymerization reactions. The reaction between activated esters and lysine amino groups is rapid and has been consistently described in almost every publication on the topic as a “random reaction”. A random reaction implies that every accessible lysine amino group on a protein molecule is equally reactive, and as a result, that the reaction is indiscriminate. Nonetheless, the literature contradicts itself by also suggesting that some lysine amino groups are more reactive than others (as a function of pKa, surface accessibility, temperature, and local environment). If the latter assumption is correct, then the outcome of these reactions cannot be random at all, and we should be able to predict the outcome from the structure of the protein. Predicting the non-random outcome of a reaction between surface lysines and reactive esters could transform the speed at which active bioconjugates can be developed and engineered. Herein, we describe a robust integrated tool that predicts the activated ester reactivity of every lysine in a protein, thereby allowing us to calculate the non-random sequence of reaction as a function of reaction conditions. Specifically, we have predicted the intrinsic reactivity of each lysine in multiple proteins with a bromine-functionalised N-hydroxysuccinimide initiator molecule. We have also shown that the model applied to PEGylation. The rules-based analysis has been coupled together in a single Python program that can bypass tedious trial and error experiments usually needed in protein-polymer conjugate design and synthesis.

A biophysical basis for the emergence of the genetic code in protocells

The origin of the genetic code is an abiding mystery in biology. Hints of a ‘code within the codons’ suggest biophysical interactions, but these patterns have resisted interpretation. Here, we present a new framework, grounded in the autotrophic growth of protocells from CO2 and H2. Recent work suggests that the universal core of metabolism recapitulates a thermodynamically favoured protometabolism right up to nucleotide synthesis. Considering the genetic code in relation to an extended protometabolism allows us to predict most codon assignments. We show that the first letter of the codon corresponds to the distance from CO2 fixation, with amino acids encoded by the purines (G followed by A) being closest to CO2 fixation. These associations suggest a purine-rich early metabolism with a restricted pool of amino acids. The second position of the anticodon corresponds to the hydrophobicity of the amino acid encoded. We combine multiple measures of hydrophobicity to show that this correlation holds strongly for early amino acids but is weaker for later species. Finally, we demonstrate that redundancy at the third position is not randomly distributed around the code: non-redundant amino acids can be assigned based on size, specifically length. We attribute this to additional stereochemical interactions at the anticodon. These rules imply an iterative expansion of the genetic code over time with codon assignments depending on both distance from CO2 and biophysical interactions between nucleotide sequences and amino acids. In this way the earliest RNA polymers could produce non-random peptide sequences with selectable functions in autotrophic protocells.

Memristive Structure-Based Chaotic System for PRNG

This paper suggests an approach to generate pseudo-random sequences based on the discrete-time model of the simple memristive chaotic system. We show that implementing Euler’s and Runge–Kutta’s methods for the simulation solutions gives the possibility of obtaining chaotic sequences that maintain general properties of the original chaotic system. A preliminary criterion based on the binary sequence balance estimation is proposed and applied to separate any binary representation of the chaotic time sequences into random and non-random parts. This gives us the possibility to delete obviously non-random sequences prior to the post-processing. The investigations were performed for arithmetic with both fixed and floating points. In both cases, the obtained sequences successfully passed the NIST SP 800-22 statistical tests. The utilization of the unidirectional asymmetric coupling of chaotic systems without full synchronization between them was suggested to increase the performance of the chaotic pseudo-random number generator (CPRNG) and avoid identical sequences on different outputs of the coupled systems. The proposed CPRNG was also implemented and tested on FPGA using Euler’s method and fixed-point arithmetic for possible usage in different applications. The FPGA implementation of CPRNG supports a generation speed up to 1.2 Gbits/s for a clock frequency of 50 MHz. In addition, we presented an example of the application of CPRNG to symmetric image encryption, but nevertheless, one is suitable for the encryption of any binary source.

Generating Randomness from a Computable, Non-Random Sequence of Qubits

Generating Randomness from a Computable, Non-Random Sequence of Qubits

Uncovering Non-random Binary Patterns Within Sequences of Intrinsically Disordered Proteins

Sequence-ensemble relationships of intrinsically disordered proteins (IDPs) are governed by binary patterns such as the linear clustering or mixing of specific residues or residue types with respect to one another. To enable the discovery of potentially important, shared patterns across sequence families, we describe a computational method referred to as NARDINI for Non-random Arrangement of Residues in Disordered Regions Inferred using Numerical Intermixing. This work was partially motivated by the observation that parameters that are currently in use for describing different binary patterns are not interoperable across IDPs of different amino acid compositions and lengths. In NARDINI, we generate an ensemble of scrambled sequences to set up a composition-specific null model for the patterning parameters of interest. We then compute a series of pattern-specific z-scores to quantify how each pattern deviates from a null model for the IDP of interest. The z-scores help in identifying putative non-random linear sequence patterns within an IDP. We demonstrate the use of NARDINI derived z-scores by identifying sequence patterns in three well-studied IDP systems. We also demonstrate how NARDINI can be deployed to study archetypal IDPs across homologs and orthologs. Overall, NARDINI is likely to aid in designing novel IDPs with a view toward engineering new sequence-function relationships or uncovering cryptic ones. We further propose that the z-scores introduced here are likely to be useful for theoretical and computational descriptions of sequence-ensemble relationships across IDPs of different compositions and lengths.

DDX41 Variant of Unknown Significance (VUS) Have Distinct Clinical and Diagnostic Features but Are Associated with Similar Prognosis and Co-Mutation Patterns As Pathogenic DDX41: Analysis of the Mayo Clinic (MC) Myeloid Next-Generation Sequencing (NGS) Cohort

Background:DDX41 gene is located on chromosome 5q35 and is believed to be a tumor suppressor gene involved in splicing of mRNA. Mutated DDX41 have been identified as germline mutation (m) in families with cases of myeloid neoplasm and have shown to cause acquisition of other somatic mutations resulting in MDS/AML. At the same time, somatic pathogenic DDX41 mutations are known to occur. Variant of unknown significance (VUS) is an intermediate tier between benign and pathogenic (path) mutations (hence uncertain) and can be re-classified based on their clinical impact. In this report we analyzed the clinical impact and relevance of DDX41VUS in patients (pts) being evaluated for myeloid disorders.Methods:We reviewed 4,524 consecutive pts who underwent NGS (MC OncoHeme 42 genes panel) testing between 2018 and 2021 performed on cases of suspected or known myeloid disorders. We identified 58 (1%) consecutive pts with DDX41VUS, among them one pt had proven concurrent DDX41 germline VUS and 7 pts with DDX41VUS had concurrent DDX41path mutation. We analyze clinical characteristics of pts with DDX41VUS and compared it with cohort of 32 DDX41path mutated pts.Results:Baseline characteristics are summarized in Table 1, and Figure 1 illustrates DDX41VUS per case with variant allele frequency (VAF) and observed concurrent mutations. The median VAF for DDX41 VUS was 48 % (range, 14-91%). Co-mutations were found in 14 (28%) pts with VUS, and the reminder (n=44, 72 %) had isolated DDX41VUS. Among them AML (16 [32%]), MDS (14 [28%]), cytopenia (14 [28%]) MPN (3 [6%]), CNL (1 [2%]) and aplastic anemia (1 [2%]) were the commonly occurring myeloid disorder (Table 1, Figure 1). Eleven of 14 pts with isolated cytopenia had isolated DDX41VUS. Conversely, among 15 evaluable pts with isolated DDX41VUS, 13 (87%) pts had normal cytogenetics and 40% of pts had family history of solid or hematological malignancies. We observed a significant difference in hematologic diagnoses: DDX41VUS patients were significantly less often diagnosed with MDS or CCUS, and more often associated with cytopenias NOS.Recurrent, non-random DDX41VUS sequences were observed; most frequent occurring amino acid change among the 58 pts were Gly173Arg (n=6), Met155lle (n=5), Pro258Leu (n=3) Arg479Gln (n=3), Val303Met (n=2), Lys331del (n=2), Arg479His (n=2) and Tyr33His (n=2) (Figure 1). 5 of 6 pts with Gly173Arg had isolated DDX41VUS, and among them 4 were diagnosed with MDS suggesting this could be a clonal event, and possible driver mutation, notable in Figure 1. The median overall survival (OS) of pts with high risk MDS/AML harboring DDX41VUS was not reached (60% alive at 2 years). Between pts with DDX41path and DDX41VUS, proportion of pts with co-mutations (p >0.99), cytogenetic abnormalities (p >0.99), family history of malignancies (p 0.52), time to treatment (p >0.99), MDS progression to AML (p 0.36) and OS (among high risk MDS/AML pts) (p 0.55) was not significantly different, suggesting that phenotypic features of DDX41VUS are similar to DDX41path , and that both carry a similar, more indolent prognosis (Table 1).Conclusion:Our reports demonstrated that DDX41VUS occurs in 1% of patients with myeloid disorders and shares distinct diagnostic features but comparable prognostic features vs. DDX41path, including family history of hematological malignancies. It is possible that many of the cases with ‘cytopenias’ and DDX41VUS would meet criteria for CCUS if the variant was isolated classified as pathogenic, confirming the importance of extending our understanding of DDX41 variants. Further analysis to characterize the biological impact of DDX41VUS is underway. [Display omitted] DisclosuresBadar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Patnaik: Kura Oncology: Research Funding; Stemline Therapeutics: Membership on an entity's Board of Directors or advisory committees; Stemline Therapeutics: Membership on an entity's Board of Directors or advisory committees. Litzow: Astellas: Research Funding; Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Pluristem: Research Funding; Amgen: Research Funding; Biosight: Other: Data monitoring committee; Actinium: Research Funding; AbbVie: Research Funding. Foran: boehringer ingelheim: Research Funding; abbvie: Research Funding; takeda: Research Funding; trillium: Research Funding; revolution medicine: Honoraria; bms: Honoraria; servier: Honoraria; novartis: Honoraria; pfizer: Honoraria; aptose: Research Funding; taiho: Honoraria; certara: Honoraria; sanofi aventis: Honoraria; syros: Honoraria; actinium: Research Funding; gamida: Honoraria; OncLive: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding.

Brain network dynamics fingerprints are resilient to data heterogeneity

Context. Large multi-site neuroimaging datasets have significantly advanced our quest to understand brain-behavior relationships and to develop biomarkers of psychiatric and neurodegenerative disorders. Yet, such data collections come at a cost, as the inevitable differences across samples may lead to biased or erroneous conclusions. Objective. We aim to validate the estimation of individual brain network dynamics fingerprints and appraise sources of variability in large resting-state functional magnetic resonance imaging (rs-fMRI) datasets by providing a novel point of view based on data-driven dynamical models. Approach. Previous work has investigated this critical issue in terms of effects on static measures, such as functional connectivity and brain parcellations. Here, we utilize dynamical models (hidden Markov models—HMM) to examine how diverse scanning factors in multi-site fMRI recordings affect our ability to infer the brain’s spatiotemporal wandering between large-scale networks of activity. Specifically, we leverage a stable HMM trained on the Human Connectome Project (homogeneous) dataset, which we then apply to an heterogeneous dataset of traveling subjects scanned under a multitude of conditions. Main Results. Building upon this premise, we first replicate previous work on the emergence of non-random sequences of brain states. We next highlight how these time-varying brain activity patterns are robust subject-specific fingerprints. Finally, we suggest these fingerprints may be used to assess which scanning factors induce high variability in the data. Significance. These results demonstrate that we can (i) use large scale dataset to train models that can be then used to interrogate subject-specific data, (ii) recover the unique trajectories of brain activity changes in each individual, but also (iii) urge caution as our ability to infer such patterns is affected by how, where and when we do so.

Structured sequences emerge from random pool when replicated by templated ligation

The central question in the origin of life is to understand how structure can emerge from randomness. The Eigen theory of replication states, for sequences that are copied one base at a time, that the replication fidelity has to surpass an error threshold to avoid that replicated specific sequences become random because of the incorporated replication errors [M. Eigen, Naturwissenschaften 58 (10), 465-523 (1971)]. Here, we showed that linking short oligomers from a random sequence pool in a templated ligation reaction reduced the sequence space of product strands. We started from 12-mer oligonucleotides with two bases in all possible combinations and triggered enzymatic ligation under temperature cycles. Surprisingly, we found the robust creation of long, highly structured sequences with low entropy. At the ligation site, complementary and alternating sequence patterns developed. However, between the ligation sites, we found either an A-rich or a T-rich sequence within a single oligonucleotide. Our modeling suggests that avoidance of hairpins was the likely cause for these two complementary sequence pools. What emerged was a network of complementary sequences that acted both as templates and substrates of the reaction. This self-selecting ligation reaction could be restarted by only a few majority sequences. The findings showed that replication by random templated ligation from a random sequence input will lead to a highly structured, long, and nonrandom sequence pool. This is a favorable starting point for a subsequent Darwinian evolution searching for higher catalytic functions in an RNA world scenario.

A universal pair of 1/2-betting strategies

We introduce a generalization of A.A. Muchnik's non-monotonic betting game, the 1/2-betting game, and show that while there is no single computable 1/2-betting strategy that wins on all Martin-Löf non-random sequences, there is a pair that does.

Generating Randomness from a Computable, Non-random Sequence of Qubits

Nies and Scholz introduced the notion of a state to describe an infinite sequence of qubits and defined quantum-Martin-Lof randomness for states, analogously to the well known concept of Martin-L\"of randomness for elements of Cantor space (the space of infinite sequences of bits). We formalize how 'measurement' of a state in a basis induces a probability measure on Cantor space. A state is 'measurement random' (mR) if the measure induced by it, under any computable basis, assigns probability one to the set of Martin-L\"of randoms. Equivalently, a state is mR if and only if measuring it in any computable basis yields a Martin-L\"of random with probability one. While quantum-Martin-L\"of random states are mR, the converse fails: there is a mR state, x which is not quantum-Martin-L\"of random. In fact, something stronger is true. While x is computable and can be easily constructed, measuring it in any computable basis yields an arithmetically random sequence with probability one. I.e., classical arithmetic randomness can be generated from a computable, non-quantum random sequence of qubits.

What Is in Umbilicaria pustulata? A Metagenomic Approach to Reconstruct the Holo-Genome of a Lichen.

Lichens are valuable models in symbiosis research and promising sources of biosynthetic genes for biotechnological applications. Most lichenized fungi grow slowly, resist aposymbiotic cultivation, and are poor candidates for experimentation. Obtaining contiguous, high-quality genomes for such symbiotic communities is technically challenging. Here, we present the first assembly of a lichen holo-genome from metagenomic whole-genome shotgun data comprising both PacBio long reads and Illumina short reads. The nuclear genomes of the two primary components of the lichen symbiosis—the fungus Umbilicaria pustulata (33 Mb) and the green alga Trebouxia sp. (53 Mb)—were assembled at contiguities comparable to single-species assemblies. The analysis of the read coverage pattern revealed a relative abundance of fungal to algal nuclei of ∼20:1. Gap-free, circular sequences for all organellar genomes were obtained. The bacterial community is dominated by Acidobacteriaceae and encompasses strains closely related to bacteria isolated from other lichens. Gene set analyses showed no evidence of horizontal gene transfer from algae or bacteria into the fungal genome. Our data suggest a lineage-specific loss of a putative gibberellin-20-oxidase in the fungus, a gene fusion in the fungal mitochondrion, and a relocation of an algal chloroplast gene to the algal nucleus. Major technical obstacles during reconstruction of the holo-genome were coverage differences among individual genomes surpassing three orders of magnitude. Moreover, we show that GC-rich inverted repeats paired with nonrandom sequencing error in PacBio data can result in missing gene predictions. This likely poses a general problem for genome assemblies based on long reads.

Reliable Sequential Activation of Neural Assemblies by Single Pyramidal Cells in a Three-Layered Cortex

Recent studies reveal the occasional impact of single neurons on surround firing statistics and even simple behaviors. Exploiting the advantages of a simple cortex, we examined the influence of single pyramidal neurons on surrounding cortical circuits. Brief activation of single neurons triggered reliable sequences of firing in tens of other excitatory and inhibitory cortical neurons, reflecting cascading activity through local networks, as indicated by delayed yet precisely timed polysynaptic subthreshold potentials. The evoked patterns were specific to the pyramidal cell of origin, extended over hundreds of micrometers from their source, and unfolded over up to 200ms. Simultaneous activation of pyramidal cell pairs indicated balanced control of population activity, preventing paroxysmal amplification. Single cortical pyramidal neurons can thus trigger reliable postsynaptic activity that can propagate in a reliable fashion through cortex, generating rapidly evolving and non-random firing sequences reminiscent of those observed in mammalian hippocampus during "replay" and in avian song circuits.

One Step up the Ladder of Prebiotic Complexity: Formation of Nonrandom Linear Polypeptides from Binary Systems of Amino Acids on Silica.

Evidence for the formation of linear oligopeptides with nonrandom sequences from mixtures of amino acids coadsorbed on silica and submitted to a simple thermal activation is presented. The amino acid couples (glutamic acid+leucine) and (aspartic acid+valine) were deposited on a fumed silica and submitted to a single heating step at moderate temperature. The evolution of the systems was characterized by X-ray diffraction, infrared spectroscopy, thermosgravimetric analysis, HPLC, and electrospray ionization mass spectrometry (ESI-MS). Evidence for the formation of amide bonds was found in all systems studied. While the products of single amino acids activation on silica could be considered as evolutionary dead ends, (glutamic acid+leucine) and, at to some extent, (aspartic acid+valine) gave rise to the high yield formation of linear peptides up to the hexamers. Oligopeptides of such length have not been observed before in surface polymerization scenarios (unless the amino acids had been deposited by chemical vapor deposition, which is not realistic in a prebiotic environment). Furthermore, not all possible amino acid sequences were present in the activation products, which is indicative of polymerization selectivity. These results are promising for origins of life studies because they suggest the emergence of nonrandom biopolymers in a simple prebiotic scenario.