Limited Sequence Research Articles

Proteins for Hyperelastic Materials.

Meticulous engineering and the yielded hyperelastic performance of structural proteins represent a new frontier in developing next-generation functional biomaterials. These materials exhibit outstanding and programmable mechanical properties, including elasticity, resilience, toughness, and active biological characteristics, such as degradability and tissue repairability, compared with their chemically synthetic counterparts. However, there are several critical issues regarding the preparation approaches of hyperelastic protein-based materials: limited natural sequence modules, non-hierarchical assembly, and imbalance between compressive and tensile elasticity, leading to unmet demands. Therefore, it is pivotal to develop an alternative strategy for biofabricating hyperelastic materials. Herein, the molecular design, engineering, and property regulation of hyperelastic structural proteins are overviewed. First, methodologies for deeper exploration of mechanical modules, including machine learning-aided de novo design, random mutations of natural sequences, and multiblock fusion techniques, are actively introduced. These methodologies facilitate the generation of elastomeric protein modules and demonstrate enhanced structural and functional versatility. Subsequently, assembly tactics of hyperelastic proteins (i.e., physical modulation, genetic adaptations, and chemical modifications) are reviewed, yielding hierarchically ordered structures. Finally, advances in biophysical techniques for more nuanced characterization of protein ensembles are discussed, unveiling the tuning mechanisms of protein elasticity across scales. Future developments in structural hyperelastic protein-based biomaterials are also envisioned.

Social context affects sequence modification learning in birdsong

Social interactions are crucial for imitative vocal learning such as human speech learning or song learning in songbirds. Recently, introducing specific learned modifications into adult song by experimenter-controlled reinforcement learning has emerged as a key protocol to study aspects of vocal learning in songbirds. This form of adult plasticity does not require conspecifics as a model for imitation or to provide social feedback on song performance. We therefore hypothesized that social interactions are irrelevant to, or even inhibit, song modification learning. We tested whether social context affects song sequence learning in adult male Bengalese finches (Lonchura striata domestica). We targeted specific syllable sequences in adult birds’ songs with negative auditory feedback, which led the birds to reduce the targeted syllable sequence in favor of alternate sequences. Changes were apparent in catch trials without feedback, indicating a learning process. Each experiment was repeated within subjects with three different social contexts (male–male, MM; male–female, MF; and male alone, MA) in randomized order. We found robust learning in all three social contexts, with a nonsignificant trend toward facilitated learning with social company (MF, MM) compared to the single-housed (MA) condition. This effect could not be explained by the order of social contexts, nor by different singing rates across contexts. Our results demonstrate that social context can influence degree of learning in adult birds even in experimenter-controlled reinforcement learning tasks, and therefore suggest that social interactions might facilitate song plasticity beyond their known role for imitation and social feedback.

Unraveling the metabolic landscape of Exophiala spinifera strain FM: Model reconstruction, insights into biodesulfurization and beyond.

Exophiala spinifera strain FM, a black yeast and melanized ascomycete, shows potential for oil biodesulfurization by utilizing dibenzothiophene (DBT) as its sole sulfur source. However, the specific pathway and enzymes involved in this process remain unclear due to limited genome sequencing and metabolic understanding of E. spinifera. In this study, we sequenced the complete genome of E. spinifera FM to construct the first genome-scale metabolic model (GSMM) for this organism. Through bioinformatics analysis, we identified genes potentially involved in DBT desulfurization and degradation pathways for hazardous pollutants. We focused on understanding the cost associated with metabolites in sulfur assimilation pathway to assess economic feasibility, optimize resource allocation, and guide metabolic engineering and process design. To overcome knowledge gaps, we developed a genome-scale model for E. spinifera, iEsp1694, enabling a comprehensive investigation into its metabolism. The model was rigorously validated against growth phenotypes and gene essentiality data. Through shadow price analysis, we identified costly metabolites such as 3'-phospho-5'-adenylyl sulfate, 5'-adenylyl sulfate, and choline sulfate when DBT was used as the sulfur source. iEsp1694 encompasses the degradation of aromatic compounds, which serves as a crucial first step in comprehending the pan metabolic capabilities of this strain.

Epigenetic Mechanisms Driving Human Evolutionary Changes

A crucial aspect of our comprehension of human evolution is epigenetics, the study of heritable modifications in gene function that do not include modifications in the DNA sequence. This intriguing field of study emphasises on how reversible and environmental-sensitive mechanisms, such as histone, DNA methylation, and non-coding RNA activity, control gene expression and support phenotypic variation. These techniques allow animals to adapt to changing environments without experiencing permanent genetic changes, providing a flexible basis for evolutionary processes. Understanding human evolution now heavily relies on epigenetics. Since animals can adapt to changing environments without enduring permanent genetic changes, evolutionary processes have a flexible basis. Epigenetic modifications have closely linked characteristics such as immune system function and brain development throughout human evolution. Epigenetic patterns have been impacted by environmental factors like diet, illness, and climate, which has allowed organisms to flourish and procreate in a variety of ecological niches. With an emphasis on their function in human evolution, this study explores the molecular mechanisms underlying epigenetic control and how epigenetics allows humans to display amazing phenotypic plasticity. The ramifications of epigenetic studies in anthropology are also examined, with a focus on how modern humans differ from their hominid ancestors and how epigenetics influences cultural and social practices. This review further highlights the revolutionary potential of epigenetics in deciphering the intricacies of human evolution by fusing knowledge from genetics, anthropology, and environmental studies.

Identification of Two Elusive Human Ribonuclease MRP-Specific Protein Components.

All known protein components of one of the longest-studied human ribonucleoprotein ribozyme nuclear Ribonuclease MRP (RNase MRP), which processes pre-rRNA at ITS1 site 2, are shared with Ribonuclease P (RNase P), which cleaves pre-tRNA 5' leader sequences. Our genome-wide forward genetic screening identified two poorly characterized human genes, which we named RPP24 and RPP64. We show that these two genes are required for pre-rRNA ITS1 site 2 processing and their protein products efficiently associate with RNA MRP. Unlike all other human RNase MRP protein components, RPP24 and RPP64 are not required for RNase P activity and do not associate with RNase P-specific RNA H1. Despite extremely limited sequence homology, RPP24 and RPP64 exhibit predicted structural similarities to two RNase MRP-specific components in S. cerevisiae , with specific differences in RPP64 regions of substrate recognition. Collectively, our functional screening and validation revealed the first two protein components unique to human nuclear RNase MRP.

Scenarios for the emergence of new miRNA genes in the plant Arabidopsis halleri.

MicroRNAs (miRNAs) are central players of the regulation of gene expression in Eukaryotes. The repertoires of miRNA genes vary drastically even among closely related species, indicating that they are evolutionarily labile. However, the processes by which they originate over the course of evolution and the nature of their progenitors across the genome remain poorly understood. Here we analyzed miRNA genes in Arabidopsis halleri, a plant species where we recently documented a large number of species-specific miRNA genes, likely to represent recent events of emergence. Analysis of sequence homology across the genome indicates that a diversity of sources contributes to the emergence of new miRNA genes, including inverted duplications from protein-coding genes, rearrangements of transposable element sequences and duplications of preexisting miRNA genes. Our observations indicate that the origin from protein-coding genes was less common than was previously considered. In contrast, we estimate that almost half of the new miRNA genes likely emerged from transposable elements. Miniature inverted transposable elements (MITE) seem to be particularly important contributors to new miRNA genes, with the Harbinger and Mariner transposable element superfamilies representing disproportionate sources for their emergence. We further analyzed the recent expansion of a miRNA family derived from MuDR elements, and the duplication of miRNA genes formed by two hAT transposons. Overall, our results illustrate the rapid pace at which new regulatory elements can arise from the modification of preexisting sequences in a genome, and highlight the central role of certain categories of transposable elements in this process.

Structural Basis of High-Precision Protein Ligation and Its Application.

Enzyme-catalyzed protein modifications have become invaluable in diverse applications, outperforming chemical methods in terms of precision, conjugation efficiency, and biological compatibility. Despite significant advances in ligases, such as sortase A and OaAEP1, their use in heterogeneous biological environments remains constrained by limited target sequence specificity. In 2021, Lupas' group introduced Connectase, a family of repurposed archaeal proteases for protein ligations, but its low processivity and lack of structural information have impeded further engineering for practical biological and biophysical applications. Here, we present the X-ray crystallographic structures of MmConnectase (Methanococcus maripaludis, MmCET) in both apo and substrate-bound forms. Comparative analysis with its inactive paralogue, MjCET (Methanococcus janaschi), reveals the structural basis of MmCET's high-precision ligation activity. We propose modifications to the N-terminal substrate recognition motifs to suppress MmCET's reversible protease activity, enabling high-precision protein ligations in complex biological environments, such as serum-containing cell cultures. To further demonstrate the enhanced processivity and precision, single-molecule protein unfolding experiments showed that our optimized Connectase, in conjunction with OaAEP1(C247A), can perform stepwise tandem ligations of protein leading to a well-defined protein polymer.

β3 accelerates microtubule plus end maturation through a divergent lateral interface.

β-tubulin isotypes exhibit similar sequences but different activities, suggesting that limited sequence divergence is functionally important. We investigated this hypothesis for TUBB3/β3, a β-tubulin linked to aggressive cancers and chemoresistance in humans. We created mutant yeast strains with β-tubulin alleles that mimic variant residues in β3 and find that residues at the lateral interface are sufficient to alter microtubule dynamics and response to microtubule targeting agents. In HeLa cells, β3 overexpression decreases the lifetime of microtubule growth, and this requires residues at the lateral interface. These microtubules exhibit a shorter region of EB binding at the plus end, suggesting faster lattice maturation, and resist stabilization by paclitaxel. Resistance requires the H1-S2 and H2-S3 regions at the lateral interface of β3. Our results identify the mechanistic origins of the unique activity of β3 tubulin and suggest that tubulin isotype expression may tune the rate of lattice maturation at growing microtubule plus ends in cells. [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text].

RNA Modification and Digestive Tract Tumors: A Review.

Gastrointestinal tumors, including colorectal and liver cancer, are among the most prevalent and lethal solid tumors. These malignancies are characterized by worsening prognoses and increasing incidence rates. Traditional therapeutic approaches often prove ineffective. Recent advancements in high-throughput sequencing and sophisticated RNA modification detection technologies have uncovered numerous RNA chemical alterations significantly associated with the pathogenesis of various diseases, notably cancer. These discoveries have opened new avenues for therapeutic intervention. This article delves into epigenetic modifications, with a particular emphasis on RNA alterations such as N6-methyladenosine (m6A), 5-methylcytosine (m5C), 1-methyladenosine (m1A), 7-methylguanosine (m7G), and N4-acetylcysteine (ac4C). It examines the functions and mechanisms of action of regulatory entities known as "Writers," "Readers," and "Erasers" to these modifications. Additionally, it outlines various methodologies for detecting these RNA modifications. Conventional techniques include radioactive isotope incorporation, two-dimensional thin-layer chromatography (2D-TLC), mass spectrometry, and immunological detection methods. Specialized methods such as bisulfite sequencing and reverse transcription stops are also discussed. Furthermore, the article underscores the significance of these modifications in the development, progression, and therapeutic targeting of gastrointestinal tumors, including esophageal, gastric, colorectal, liver, and pancreatic cancers. This exploration provides foundational insights for enhancing diagnostic accuracy, treatment efficacy, and prognostic assessment in gastrointestinal oncology.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost.

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

Phenotypic and genotypic characterization of clinical carbapenem-resistant Acinetobacter species harboring the metallo-beta-lactamases IMP-8 or NDM-1 in China.

Given the low prevalence of IMP among A. baumannii and the limited sequencing technology in earlier years, research on blaIMP in A. baumannii is scarce, and genetic information on blaNDM-1-producing Acinetobacter spp. strains isolated in earlier years is limited. This study revisited five MBL-carrying Acinetobacter spp. strains isolated in 2010, characterizing their phenotypic and genotypic features. This retrospective analysis serves as a form of "bacterial archaeology," providing evidence of the evolutionary changes in genetic elements conferring antibiotic resistance.

Key Features to Improve CRISPR sgRNA Efficacy

The CRISPR-Cas9 system has revolutionized genome editing by enabling precise and efficient modification of genetic sequences. However, the efficacy and specificity of this system largely depend on the design and optimization of single guide RNA (sgRNA). Effective sgRNA design requires consideration of several factors, including sequence specificity, GC content, secondary structure formation, and proximity to the protospacer adjacent motif (PAM). These factors influence the binding stability of the sgRNA to the target DNA and the cleavage efficiency of the Cas9 protein. Additionally, minimizing off-target effects is crucial for ensuring the precision of genome editing. This can be achieved through the use of computational tools to predict potential off-target sites, optimization of sgRNA length, and employing engineered Cas9 variants such as high-fidelity Cas9 (HiFi-Cas9) and Cas9-HF1, which offer improved specificity. Experimental factors, including the delivery method of the CRISPR components and the choice of the Cas protein variant, also play a critical role in determining overall efficacy. Advances in understanding the biophysical and biochemical interactions of sgRNA, along with continuous improvements in computational prediction tools and Cas9 engineering, have significantly enhanced the reliability and scope of CRISPR applications. This review provides an in-depth discussion of the critical features influencing sgRNA efficacy and highlights emerging strategies to optimize CRISPR-Cas9-based genome editing for research and therapeutic purposes. Keywords : CRISPR-Cas9, genome editing, single guide RNA (sgRNA), sequence specificity, GC content, secondary structure, protospacer adjacent motif (PAM), off-target effects, computational tools, sgRNA optimization, high-fidelity Cas9 (HiFi-Cas9), Cas9-HF1, Cas protein variants

Quantification of Staphylococcal Enterotoxin A Variants at Low Level in Dairy Products by High-Resolution Top-Down Mass Spectrometry.

Food poisoning outbreaks frequently involve staphylococcal enterotoxins (SEs). SEs include 33 distinct types and multiple sequence variants per SE type. Various mass spectrometry methods have been reported for the detection of SEs using a conventional bottom-up approach. However, the bottom-up approach cannot differentiate between all sequence variants due to partial sequence coverage, and it requires a long trypsin digestion time. While the alternative top-down approach can theoretically identify any sequence modifications, it generally provides lower sensitivity. In this study, we optimized top-down mass spectrometry conditions and incorporated a fully 15N-labeled SEA spiked early in the protocol to achieve sensitivity and repeatability comparable to bottom-up approaches. After robust immunoaffinity purification of the SEA, mass spectrometry signals were acquired on a Q-Orbitrap instrument operated in full-scan mode and targeted acquisition by parallel reaction monitoring (PRM), enabling the identification of sequence variants and precise quantification of SEA. The protocol was evaluated in liquid and solid dairy products and demonstrated detection limits of 0.5 ng/mL or ng/g in PRM and 1 ng/mL or ng/g in full-scan mode for milk and Roquefort cheese. The top-down method was successfully applied to various dairy products, allowing discrimination of contaminated versus non-contaminated food, quantification of SEA level and identification of the variant involved.

Improved precision, sensitivity, and adaptability of ordered two-template relay cDNA library preparation for RNA sequencing.

Sequencing RNAs that are biologically processed or degraded to less than ∼100 nt typically involves multistep, low-yield protocols with bias and information loss inherent to ligation and/or polynucleotide tailing. We recently introduced ordered two-template relay (OTTR), a method that captures obligatorily end-to-end sequences of input molecules and, in the same reverse transcription step, also appends 5' and 3' sequencing adapters of choice. OTTR has been thoroughly benchmarked for optimal production of microRNA, tRNA and tRNA fragments, and ribosome-protected mRNA footprint libraries. Here we sought to characterize, quantify, and ameliorate any remaining bias or imprecision in the end-to-end capture of RNA sequences. We introduce new metrics for the evaluation of sequence capture and use them to optimize reaction buffers, reverse transcriptase sequence, adapter oligonucleotides, and overall workflow. Modifications of the reverse transcriptase and adapter oligonucleotides increased the 3' and 5' end-precision of sequence capture and minimized overall library bias. Improvements in recombinant expression and purification of the truncated Bombyx mori R2 reverse transcriptase used in OTTR reduced nonproductive sequencing reads by minimizing bacterial nucleic acids that compete with low-input RNA molecules for cDNA synthesis, such that with miRNA input of 3 pg (<1 fmol), fewer than 10% of sequencing reads are bacterial nucleic acid contaminants. We also introduce a rapid, automation-compatible OTTR protocol that enables gel-free, length-agnostic enrichment of cDNA duplexes from unwanted adapter-only side products. Overall, this work informs considerations for unbiased end-to-end capture and annotation of RNAs independent of their sequence, structure, or posttranscriptional modifications.

A Study on the Treatment of Rheumatoid Arthritis with Lipid Nanoparticles Containing mRNA encoding Heat shock protein 10.

In order to delay the progression of Rheumatoid Arthritis (RA) in patients, and to prevent further teratogenesis and irreversible bone erosion through drug intervention in the early stages of inflammation, this experiment used the mRNA encoding heat shock protein 10 (HSP10) (H-mRNA) as the main therapeutic drug and used Microfluidics technology to prepare lipid nanoparticles (LNP) (H-mRNA LNPs) containing H-mRNA, and the surface of H-mRNA-LNPs was modified using heparin particals to obtain the final formulation H-mRNA-LNPs @ heparin/ Protamine. Through the sequence modification and effect evaluation of H-mRNA, we explored the formulation screening, physical characterization, cytotoxicity in vitro, distribution in vivo, pharmacodynamics in vivo, and safety in vivo of the prepared lipid nanoparticles, which proved that this nano-preparation had good anti Rheumatoid Arthritis effects, and conducted a preliminary exploration for the application of nucleic acid drugs in the treatment of diseases outside of tumors. This research would provide new ideas for the treatment of RA.

Characterization of the BH1406 non-small cell lung cancer (NSCLC) cell line carrying an activating SOS1 mutation.

Approximately 30% of the non-small cell lung cancer (NSCLC) patients which harbor no recognizable oncogenic driver mutation are not eligible for targeted therapy. Functional drug screening of tumor cells helps to identify susceptible drug targets not recognized by gene panels for targeted mutation analysis. The aim of this study is to characterize the BH1406 cell line carrying an activating SOS1 mutation and to check its sensitivity to cognate inhibitors. The NSCLC cell line BH1406 was established from a pleural effusion and found to be sensitive to the SOS1 inhibitor BAY-293 in initial viability screenings. Since in a limited next-generation sequencing (NGS) lung cancer mutation panel no driver could be detected, the patient underwent chemotherapy with poor outcome. This cell line was further characterized by exome sequencing, SOS1 Western blotting, comparison of two-dimensional (2D) and three-dimensional (3D) chemosensitivity assays and phosphoprotein arrays. In whole-exome sequencing (WES) the SOS1 mutation P481delinsLFFL, positioned near the known P478L activating mutation was detected. Besides BAY-293, BH1406 cells proved to be sensitive to the SOS1 inhibitors MRTX0902 and BI-3406. The sensitivity of BH1406 cells to BI-3406 was increased under 3D conditions compared to 2D cultures. Western blot phosphoprotein arrays revealed reduced phosphorylation of CREB, GSK3, CHK-2 and STAT3 in BH1406 by BAY-293 treatment in 2D culture. In 3D conditions, cells switched from GSK3α to elevated ERK1/2 signaling, again blocked by the SOS1 inhibitor BAY-293. Similar results were obtained for the SOS1 inhibitors MRTX0902 and BI3406. Additionally, the PI3K inhibitor dactolisib, the GSK-3 inhibitor BI-5521 as well as the bromodomain protein-directed PROTAC ARV-771 inhibited the growth of BH1406 cells significantly and showed synergistic interaction with BAY-293. Furthermore, Western blots demonstrated reduced expression of SOS1 and MYC proteins in response to BAY-293 treatment. The rare SOS1 P481delinsLFFL mutation in lung cancer may be targetable with corresponding inhibitors, alone or in combination with GSK3/PI3K/BET inhibitors. BH1406 cells represent a novel cellular model suitable for the molecular characterization of SOS1 druggability. Such rare oncogenic driver genes are not included in standard NGS panels and need to be detected by expanded assays like WES.

Dissecting AlphaFold2's capabilities with limited sequence information.

Protein structure prediction aims to infer a protein's three-dimensional (3D) structure from its amino acid sequence. Protein structure is pivotal for elucidating protein functions, interactions, and driving biotechnological innovation. The deep learning model AlphaFold2, has revolutionized this field by leveraging phylogenetic information from multiple sequence alignments (MSAs) to achieve remarkable accuracy in protein structure prediction. However, a key question remains: how well does AlphaFold2 understand protein structures? This study investigates AlphaFold2's capabilities when relying primarily on high-quality template structures, without the additional information provided by MSAs. By designing experiments that probe local and global structural understanding, we aimed to dissect its dependence on specific features and its ability to handle missing information. Our findings revealed AlphaFold2's reliance on sterically valid C for correctly interpreting structural templates. Additionally, we observed its remarkable ability to recover 3D structures from certain perturbations and the negligible impact of the previous structure in recycling. Collectively, these results support the hypothesis that AlphaFold2 has learned an accurate biophysical energy function. However, this function seems most effective for local interactions. Our work advances understanding of how deep learning models predict protein structures and provides guidance for researchers aiming to overcome limitations in these models. Data and implementation are available at https://github.com/ibmm-unibe-ch/template-analysis.

Estimation of PfRh5-based vaccine efficacy in asymptomatic Plasmodium falciparum patients from high-endemic areas of Tanzania using genetic and antigenicity variation screening.

Plasmodium falciparum is the most lethal malaria parasite. Recent phase 1b vaccine trials using P. falciparum reticulocyte binding protein homolog 5 (PfRh5) demonstrated safety and promising efficacy in preventing merozoite invasion. PfRh5 has emerged as a strong vaccine candidate due to its essential role in merozoite invasion and limited sequence variation. For effective malaria vaccine development, especially in high-transmission settings, strain-transcending activity must be considered. Ongoing monitoring of antigenic variation and natural immune responses is important to estimate vaccine efficacy across geographically diverse populations. Samples for this study were collected from four villages in each of the Kigoma and Geita regions, known malaria transmission hotspots in Tanzania. This community-based cross-sectional study was conducted from December 2022 to July 2023. Genetic variation and natural selection pressure on pfrh5 were analyzed in 164 asymptomatic P. falciparum isolates. The humoral immune response to PfRh5 was also assessed using a protein microarray with 242 sera samples from asymptomatic patients in the same population. Finally, a correlation analysis was conducted to compare pfrh5 genetic variation with the humoral immune response. The results revealed that pfrh5 was well conserved, but novel non-synonymous mutations were found at D65H, H170N, and I227M. Additionally, natural selection metrics indicated the potential for positive selection and a recent population expansion of PfRh5 in the study area, both of which could influence vaccine effectiveness. Antigenicity screening revealed variable sensitivity, ranging from 3.3% in Bunyambo to 82.8% in Rwantaba, with no significant relationship between antigenicity and parasitemia, haplotypes, or gender. However, age was significantly associated with humoral immune response (ρ = 0.170, p = 0.008). These findings underscore the need for future PfRh5-based vaccines to consider for increasing genetic variation and geographical differences in humoral immune responses.

Structural Transition Analysis of Bilayer Black Phosphorus under High Pressure via Ultralow-Frequency Raman Spectroscopy.

The unique anisotropic electron-photon and electron-phonon interactions of black phosphorus (BP) set it apart from other isotropic 2D materials. These anisotropic properties can be adjusted by varying the stacking thickness and sequence as well as by applying external pressure and strain. In contrast to multilayer or bulk BP, the effects of pressure on bilayer BP are still not fully elucidated. This study presents experimental evidence that explores the high-pressure response (0-20 GPa) of bilayer BP within the extreme low Raman shift region (5-150 cm-1), aiming at verifying structural phase transitions and stacking sequence variations. Notably, phase transitions were observed at ∼7 GPa for the orthorhombic to rhombohedral transition and at ∼14-16 GPa for a further transition to a simple cubic structure. The effects of pressure on bilayer BP with three distinct stacking sequences (AA, AB, and AC) were analyzed using angular-resolved polarized Raman spectroscopy (ARPR). The recovery of all characteristic Raman modes after the application of pressure substantiates the reversibility of the structural phase transitions in bilayer BP across all three stacking sequences. However, significant alterations in the stacking sequences were observed before and after the application of hydrostatic pressure. Specifically, AA and AC stacking sequences showed a tendency to relax into an optimized interlayer AB stacking structure upon the release of pressure from 20 to 0 GPa. This observed change in the stacking sequences of bilayer BP under pressure is detected for the first time in this work. The pressure-induced modifications in the stacking sequences, and consequently in the anisotropic properties of bilayer BP, highlight its potential as a promising material for pressure- (or strain-) sensitive optoelectronic nanodevices. Additionally, this study offers novel insights into the analysis of anisotropic interlayer interactions in other van der Waals-stacked 2D materials.

Improved precision, sensitivity, and adaptability of Ordered Two-Template Relay cDNA library preparation for RNA sequencing.

Sequencing RNAs that are biologically processed or degraded to less than ~100 nucleotides typically involves multi-step, low-yield protocols with bias and information loss inherent to ligation and/or polynucleotide tailing. We recently introduced Ordered Two-Template Relay (OTTR), a method that captures obligatorily end-to-end sequences of input molecules and, in the same reverse transcription step, also appends 5' and 3' sequencing adapters of choice. OTTR has been thoroughly benchmarked for optimal production of microRNA, tRNA and tRNA fragments, and ribosome-protected mRNA footprint libraries. Here we sought to characterize, quantify, and ameliorate any remaining bias or imprecision in the end-to-end capture of RNA sequences. We introduce new metrics for the evaluation of sequence capture and use them to optimize reaction buffers, reverse transcriptase sequence, adapter oligonucleotides, and overall workflow. Modifications of the reverse transcriptase and adapter oligonucleotides increased the 3' and 5' end-precision of sequence capture and minimized overall library bias. Improvements in recombinant expression and purification of the truncated Bombyx mori R2 reverse transcriptase used in OTTR reduced non-productive sequencing reads by minimizing bacterial nucleic acids that compete with low-input RNA molecules for cDNA synthesis, such that with miRNA input of 3 picograms (less than 1 fmol), fewer than 10% of sequencing reads are bacterial nucleic acid contaminants. We also introduce a rapid, automation-compatible OTTR protocol that enables gel-free, length-agnostic enrichment of cDNA duplexes from unwanted adapter-only side products. Overall, this work informs considerations for unbiased end-to-end capture and annotation of RNAs independent of their sequence, structure, or post-transcriptional modifications.