A Site of Vulnerability on the Influenza Virus Hemagglutinin Head Domain Trimer Interface.

Here, we describe the discovery of a naturally occurring human antibody (Ab), FluA-20, that recognizes a new site of vulnerability on the hemagglutinin (HA) head domain and reacts with most influenza A viruses. Structural characterization of FluA-20 with H1 and H3 head domains revealed a novel epitope in the HA trimer interface, suggesting previously unrecognized dynamic features of the trimeric HA protein. The critical HA residues recognized by FluA-20 remain conserved across most subtypes of influenza A viruses, which explains the Ab's extraordinary breadth. The Ab rapidly disrupted the integrity of HA protein trimers, inhibited cell-to-cell spread of virus in culture, and protected mice against challenge with viruses of H1N1, H3N2, H5N1, or H7N9 subtypes when used as prophylaxis or therapy. The FluA-20 Ab has uncovered an exceedingly conserved protective determinant in the influenza HA head domain trimer interface that is an unexpected new target for anti-influenza therapeutics and vaccines.

Lung mesenchymal cells elicit lipid storage in neutrophils that fuel breast cancer lung metastasis.

Acquisition of a lipid-laden phenotype by immune cells has been defined in infectious diseases and atherosclerosis but remains largely uncharacterized in cancer. Here, in breast cancer models, we found that neutrophils are induced to accumulate neutral lipids upon interaction with resident mesenchymal cells in the premetastatic lung. Lung mesenchymal cells elicit this process through repressing the adipose triglyceride lipase (ATGL) activity in neutrophils in prostaglandin E2-dependent and -independent manners. In vivo, neutrophil-specific deletion of genes encoding ATGL or ATGL inhibitory factors altered neutrophil lipid profiles and breast tumor lung metastasis in mice. Mechanistically, lipids stored in lung neutrophils are transported to metastatic tumor cells through a macropinocytosis-lysosome pathway, endowing tumor cells with augmented survival and proliferative capacities. Pharmacological inhibition of macropinocytosis significantly reduced metastatic colonization by breast tumor cells in vivo. Collectively, our work reveals that neutrophils serve as an energy reservoir to fuel breast cancer lung metastasis.

Sequencing of N6-methyl-deoxyadenosine at single-base resolution across the mammalian genome.

Although DNA N6-methyl-deoxyadenosine (6mA) is abundant in bacteria and protists, its presence and function in mammalian genomes have been less clear. We present Direct-Read 6mA sequencing (DR-6mA-seq), an antibody-independent method, to measure 6mA at base resolution. DR-6mA-seq employs a unique mutation-based strategy to reveal 6mA sites as misincorporation signatures without any chemical or enzymatic modulation of 6mA. We validated DR-6mA-seq through the successful mapping of the well-characterized G(6mA)TC motif in the E. coli DNA. As expected, when applying DR-6mA-seq to mammalian systems, we found that genomic DNA (gDNA) 6mA abundance is generally low in most mammalian tissues and cells; however, we did observe distinct gDNA 6mA sites in mouse testis and glioblastoma cells. DR-6mA-seq provides an enabling tool to detect 6mA at single-base resolution for a comprehensive understanding of DNA 6mA in eukaryotes.

2'-O-methylation at internal sites on mRNA promotes mRNA stability.

2'-O-methylation (Nm) is a prominent RNA modification well known in noncoding RNAs and more recently also found at many mRNA internal sites. However, their function and base-resolution stoichiometry remain underexplored. Here, we investigate the transcriptome-wide effect of internal site Nm on mRNA stability. Combining nanopore sequencing with our developed machine learning method, NanoNm, we identify thousands of Nm sites on mRNAs with a single-base resolution. We observe a positive effect of FBL-mediated Nm modification on mRNA stability and expression level. Elevated FBL expression in cancer cells is associated with increased expression levels for 2'-O-methylated mRNAs of cancer pathways, implying the role of FBL in post-transcriptional regulation. Lastly, we find that FBL-mediated 2'-O-methylation connects to widespread 3' UTR shortening, a mechanism that globally increases RNA stability. Collectively, we demonstrate that FBL-mediated Nm modifications at mRNA internal sites regulate gene expression by enhancing mRNA stability.

Analysis of a Therapeutic Antibody Cocktail Reveals Determinants for Cooperative and Broad Ebolavirus Neutralization.

Structural principles underlying the composition of protective antiviral monoclonal antibody (mAb) cocktails are poorly defined. Here, we exploited antibody cooperativity to develop a therapeutic mAb cocktail against Ebola virus. We systematically analyzed the antibody repertoire in human survivors and identified a pair of potently neutralizing mAbs that cooperatively bound to the ebolavirus glycoprotein (GP). High-resolution structures revealed that in a two-antibody cocktail, molecular mimicry was a major feature of mAb-GP interactions. Broadly neutralizing mAb rEBOV-520 targeted a conserved epitope on the GP base region. mAb rEBOV-548 bound to a glycan cap epitope, possessed neutralizing and Fc-mediated effector function activities, and potentiated neutralization by rEBOV-520. Remodeling of the glycan cap structures by the cocktail enabled enhanced GP binding and virus neutralization. The cocktail demonstrated resistance to virus escape and protected non-human primates (NHPs) against Ebola virus disease. These data illuminate structural principles of antibody cooperativity with implications for development of antiviral immunotherapeutics.

Anomalous intense coherent secondary photoemission from a perovskite oxide.

Photocathodes-materials that convert photons into electrons through a phenomenon known as the photoelectric effect-are important for many modern technologies that rely on light detection or electron-beam generation1-3. However, current photocathodes are based on conventional metals and semiconductors that were mostly discovered six decades ago with sound theoretical underpinnings4,5. Progress in this field has been limited to refinements in photocathode performance based on sophisticated materials engineering1,6. Here we report unusual photoemission properties of the reconstructed surface of single crystals of the perovskite oxide SrTiO3(100), which were prepared by simple vacuum annealing. These properties are different from the existing theoretical descriptions4,7-10. In contrast to other photocathodes with a positive electron affinity, our SrTiO3 surface produces, at room temperature, discrete secondary photoemission spectra, which are characteristic of efficient photocathode materials with a negative electron affinity11,12. At low temperatures, the photoemission peak intensity is enhanced substantially and the electron beam obtained from non-threshold excitations shows longitudinal and transverse coherence that differs from previous results by at least an order of magnitude6,13,14. The observed emergence of coherence in secondary photoemission points to the development of a previously undescribed underlying process in addition to those of the current theoretical photoemission framework. SrTiO3 is an example of a fundamentally new class of photocathode quantum materials that could be used for applications that require intense coherent electron beams, without the need for monochromatic excitations.

Dopamine Uses the DRD5-ARRB2-PP2A Signaling Axis to Block the TRAF6-Mediated NF-κB Pathway and Suppress Systemic Inflammation.

The functional relevance and mechanistic basis of the effects of the neurotransmitter dopamine (DA) on inflammation remain unclear. Here we reveal that DA inhibited TLR2-induced NF-κB activation and inflammation via the DRD5 receptor in macrophages. We found that the DRD5 receptor, via the EFD and IYX(X)I/L motifs in its CT and IC3 loop, respectively, can directly recruit TRAF6 and its negative regulator ARRB2 to form a multi-protein complex also containing downstream signaling proteins, such as TAK1, IKKs, and PP2A, that impairs TRAF6-mediated activation of NF-κB and expression of pro-inflammatory genes. Furthermore, the DA-DRD5-ARRB2-PP2A signaling axis can prevent S. aureus-induced inflammation and protect mice against S. aureus-induced sepsis and meningitis after DA treatment. Collectively, these findings provide the first demonstration of DA-DRD5 signaling acting to control inflammation and a detailed delineation of the underlying mechanism and identify the DRD5-ARRB2-PP2A axis as a potential target for future therapy of inflammation-associated diseases such as meningitis and sepsis.

N6-Deoxyadenosine Methylation in Mammalian Mitochondrial DNA.

N6-Methyldeoxyadenosine (6mA) has recently been shown to exist and play regulatory roles in eukaryotic genomic DNA (gDNA). However, the biological functions of 6mA in mammals have yet to be adequately explored, largely due to its low abundance in most mammalian genomes. Here, we report that mammalian mitochondrial DNA (mtDNA) is enriched for 6mA. The level of 6mA in HepG2 mtDNA is at least 1,300-fold higher than that in gDNA under normal growth conditions, corresponding to approximately four 6mA modifications on each mtDNA molecule. METTL4, a putative mammalian methyltransferase, can mediate mtDNA 6mA methylation, which contributes to attenuated mtDNA transcription and a reduced mtDNA copy number. Mechanistically, the presence of 6mA could repress DNA binding and bending by mitochondrial transcription factor (TFAM). Under hypoxia, the 6mA level in mtDNA could be further elevated, suggesting regulatory roles for 6mA in mitochondrial stress response. Our study reveals DNA 6mA as a regulatory mark in mammalian mtDNA.

E93 is indispensable for reproduction in ametabolous and hemimetabolous insects.

Ecdysone-induced protein 93 (E93), known as the 'adult-specifier' transcription factor in insects, triggers metamorphosis in both hemimetabolous and holometabolous insects. Although E93 is conserved in ametabolous insects, its spatiotemporal expression and physiological function remain poorly understood. In this study, we first discover that, in the ametabolous firebrat Thermobia domestica, the previtellogenic ovary exhibits cyclically high E93 expression, and E93 mRNA is broadly distributed in previtellogenic ovarioles. E93 homozygous mutant females of T. domestica exhibit severe fecundity deficiency due to impaired previtellogenic development of the ovarian follicles, likely because E93 induces the expression of genes involved in ECM (extracellular matrix)-receptor interactions during previtellogenesis. Moreover, we reveal that in the hemimetabolous cockroach Blattella germanica, E93 similarly promotes previtellogenic ovarian development. In addition, E93 is also essential for vitellogenesis that is necessary to guarantee ovarian maturation and promotes the vitellogenesis-previtellogenesis switch in the fat body of adult female cockroaches. Our findings deepen the understanding of the roles of E93 in controlling reproduction in insects, and of E93 expression and functional evolution, which are proposed to have made crucial contributions to the origin of insect metamorphosis.

Transcriptome-wide Mapping of Internal N7-Methylguanosine Methylome in Mammalian mRNA.

N7-methylguanosine (m7G) is a positively charged, essential modification at the 5' cap of eukaryotic mRNA, regulating mRNA export, translation, and splicing. m7G also occurs internally within tRNA and rRNA, but its existence and distribution within eukaryotic mRNA remain to be investigated. Here, we show the presence of internal m7G sites within mammalian mRNA. We then performed transcriptome-wide profiling of internal m7G methylome using m7G-MeRIP sequencing (MeRIP-seq). To map this modification at base resolution, we developed a chemical-assisted sequencing approach that selectively converts internal m7G sites into abasic sites, inducing misincorporation at these sites during reverse transcription. This base-resolution m7G-seq enabled transcriptome-wide mapping of m7G in human tRNA and mRNA, revealing distribution features of the internal m7G methylome in human cells. We also identified METTL1 as a methyltransferase that installs a subset of m7G within mRNA and showed that internal m7G methylation could affect mRNA translation.

Using global remote camera data of a solitary species complex to evaluate the drivers of group formation.

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.

Chemical manipulation of m1A mediates its detection in human tRNA.

N 1-methyl adenosine (m1A) is a widespread RNA modification present in tRNA, rRNA, and mRNA. m1A modification sites in tRNAs are evolutionarily conserved and its formation on tRNA is catalyzed by methyltransferase TRMT61A and TRMT6 complex. m1A promotes translation initiation and elongation. Due to its positive charge under physiological conditions, m1A can notably modulate RNA structure. It also blocks Watson-Crick-Franklin base-pairing and causes mutation and truncation during reverse transcription. Several misincorporation-based high-throughput sequencing methods have been developed to sequence m1A. In this study, we introduce a reduction-based m1A sequencing (red-m1A-seq). We report that NaBH4 reduction of m1A can improve the mutation and readthrough rates using commercially available RT enzymes to give a better positive signature, while alkaline-catalyzed Dimroth rearrangement can efficiently convert m1A to m6A to provide good controls, allowing the detection of m1A with higher sensitivity and accuracy. We applied red-m1A-seq to sequence human small RNA, and we not only detected all the previously reported tRNA m1A sites, but also new m1A sites in mt-tRNAAsn-GTT and 5.8S rRNA.

Mmp-induced fat body cell dissociation promotes pupal development and moderately averts pupal diapause by activating lipid metabolism.

In Lepidoptera and Diptera, the fat body dissociates into single cells in nondiapause pupae, but it does not dissociate in diapause pupae until diapause termination. Using the cotton bollworm, Helicoverpa armigera, as a model of pupal diapause insects, we illustrated the catalytic mechanism and physiological importance of fat body cell dissociation in regulating pupal development and diapause. In nondiapause pupae, cathepsin L (CatL) activates matrix metalloproteinases (Mmps) that degrade extracellular matrix proteins and cause fat body cell dissociation. Mmp-induced fat body cell dissociation activates lipid metabolism through transcriptional regulation, and the resulting energetic supplies increase brain metabolic activity (i.e., mitochondria respiration and insulin signaling) and thus promote pupal development. In diapause pupae, low activities of CatL and Mmps prevent fat body cell dissociation and lipid metabolism from occurring, maintaining pupal diapause. Importantly, as demonstrated by chemical inhibitor treatments and CRISPR-mediated gene knockouts, Mmp inhibition delayed pupal development and moderately increased the incidence of pupal diapause, while Mmp stimulation promoted pupal development and moderately averted pupal diapause. This study advances our recent understanding of fat body biology and insect diapause regulation.

A novel gain-of-function phosphorylation site modulates PTPN22 inhibition of TCR signaling.

Protein tyrosine phosphatase nonreceptor type 22 (PTPN22) is encoded by a major autoimmunity gene and is a known inhibitor of T cell receptor (TCR) signaling and drug target for cancer immunotherapy. However, little is known about PTPN22 posttranslational regulation. Here, we characterize a phosphorylation site at Ser325 situated C terminal to the catalytic domain of PTPN22 and its roles in altering protein function. In human T cells, Ser325 is phosphorylated by glycogen synthase kinase-3 (GSK3) following TCR stimulation, which promotes its TCR-inhibitory activity. Signaling through the major TCR-dependent pathway under PTPN22 control was enhanced by CRISPR/Cas9-mediated suppression of Ser325 phosphorylation and inhibited by mimicking it via glutamic acid substitution. Global phospho-mass spectrometry showed Ser325 phosphorylation state alters downstream transcriptional activity through enrichment of Swi3p, Rsc8p, and Moira domain binding proteins, and next-generation sequencing revealed it differentially regulates the expression of chemokines and T cell activation pathways. Moreover, in vitro kinetic data suggest the modulation of activity depends on a cellular context. Finally, we begin to address the structural and mechanistic basis for the influence of Ser325 phosphorylation on the protein's properties by deuterium exchange mass spectrometry and NMR spectroscopy. In conclusion, this study explores the function of a novel phosphorylation site of PTPN22 that is involved in complex regulation of TCR signaling and provides details that might inform the future development of allosteric modulators of PTPN22.

AMPK activates the Nrf2-Keap1 pathway to govern dendrite pruning via the insulin pathway in Drosophila.

During Drosophila metamorphosis, the ddaC dendritic arborisation sensory neurons selectively prune their larval dendrites in response to steroid hormone ecdysone signalling. The Nrf2-Keap1 pathway acts downstream of ecdysone signalling to promote proteasomal degradation and thereby dendrite pruning. However, how the Nrf2-Keap1 pathway is activated remains largely unclear. Here, we demonstrate that the metabolic regulator AMP-activated protein kinase (AMPK) plays a cell-autonomous role in dendrite pruning. Importantly, AMPK is required for Mical and Headcase expression and for activation of the Nrf2-Keap1 pathway. We reveal that AMPK promotes the Nrf2-Keap1 pathway and dendrite pruning partly via inhibition of the insulin pathway. Moreover, the AMPK-insulin pathway is required for ecdysone signalling to activate the Nrf2-Keap1 pathway during dendrite pruning. Overall, this study reveals an important mechanism whereby ecdysone signalling activates the Nrf2-Keap1 pathway via the AMPK-insulin pathway to promote dendrite pruning, and further suggests that during the nonfeeding prepupal stage metabolic alterations lead to activation of the Nrf2-Keap1 pathway and dendrite pruning.

Nutrition-dependent juvenile hormone sensitivity promotes flight-muscle degeneration during the aphid dispersal-reproduction transition.

In insects, the loss of flight typically involves a dispersal-reproduction transition, but the underlying molecular mechanisms remain poorly understood. In the parthenogenetic pea aphid Acyrthosiphon pisum, winged females undergo flight-muscle degeneration after flight and feeding on new host plants. Similarly, topical application of a juvenile hormone (JH) mimic to starved aphids also induces flight-muscle degeneration. We found that feeding preferentially upregulated the expression of the JH receptor gene Met and a JH-inducible gene, Kr-h1, in the flight muscles, and, thus, enhanced tissue-specific JH sensitivity and signaling. RNAi-mediated knockdown of Kr-h1 prevented flight-muscle degeneration. Likewise, blocking nutritional signals by pharmacological inhibition of the target of rapamycin complex 1 (TORC1) impaired JH sensitivity of the flight muscles in feeding aphids and subsequently delayed muscle degeneration. RNA-sequencing analysis revealed that enhanced JH signaling inhibited the transcription of genes involved in the tricarboxylic acid cycle, likely resulting in reduction of the energy supply, mitochondrial dysfunction and muscle-fiber breakdown. This study shows that nutrient-dependent hormone sensitivity regulates developmental plasticity in a tissue-specific manner, emphasizing a relatively underappreciated mechanism of hormone sensitivity in modulating hormone signaling.

Alignment-free estimation of sequence conservation for identifying functional sites using protein sequence embeddings.

Protein language modeling is a fast-emerging deep learning method in bioinformatics with diverse applications such as structure prediction and protein design. However, application toward estimating sequence conservation for functional site prediction has not been systematically explored. Here, we present a method for the alignment-free estimation of sequence conservation using sequence embeddings generated from protein language models. Comprehensive benchmarks across publicly available protein language models reveal that ESM2 models provide the best performance to computational cost ratio for conservation estimation. Applying our method to full-length protein sequences, we demonstrate that embedding-based methods are not sensitive to the order of conserved elements-conservation scores can be calculated for multidomain proteins in a single run, without the need to separate individual domains. Our method can also identify conserved functional sites within fast-evolving sequence regions (such as domain inserts), which we demonstrate through the identification of conserved phosphorylation motifs in variable insert segments in protein kinases. Overall, embedding-based conservation analysis is a broadly applicable method for identifying potential functional sites in any full-length protein sequence and estimating conservation in an alignment-free manner. To run this on your protein sequence of interest, try our scripts at https://github.com/esbgkannan/kibby.

Tree visualizations of protein sequence embedding space enable improved functional clustering of diverse protein superfamilies.

Protein language models, trained on millions of biologically observed sequences, generate feature-rich numerical representations of protein sequences. These representations, called sequence embeddings, can infer structure-functional properties, despite protein language models being trained on primary sequence alone. While sequence embeddings have been applied toward tasks such as structure and function prediction, applications toward alignment-free sequence classification have been hindered by the lack of studies to derive, quantify and evaluate relationships between protein sequence embeddings. Here, we develop workflows and visualization methods for the classification of protein families using sequence embedding derived from protein language models. A benchmark of manifold visualization methods reveals that Neighbor Joining (NJ) embedding trees are highly effective in capturing global structure while achieving similar performance in capturing local structure compared with popular dimensionality reduction techniques such as t-SNE and UMAP. The statistical significance of hierarchical clusters on a tree is evaluated by resampling embeddings using a variational autoencoder (VAE). We demonstrate the application of our methods in the classification of two well-studied enzyme superfamilies, phosphatases and protein kinases. Our embedding-based classifications remain consistent with and extend upon previously published sequence alignment-based classifications. We also propose a new hierarchical classification for the S-Adenosyl-L-Methionine (SAM) enzyme superfamily which has been difficult to classify using traditional alignment-based approaches. Beyond applications in sequence classification, our results further suggest NJ trees are a promising general method for visualizing high-dimensional data sets.

Using explainable machine learning to uncover the kinase-substrate interaction landscape.

MOTIVATION: Phosphorylation, a post-translational modification regulated by protein kinase enzymes, plays an essential role in almost all cellular processes. Understanding how each of the nearly 500 human protein kinases selectively phosphorylates their substrates is a foundational challenge in bioinformatics and cell signaling. Although deep learning models have been a popular means to predict kinase-substrate relationships, existing models often lack interpretability and are trained on datasets skewed toward a subset of well-studied kinases. RESULTS: Here we leverage recent peptide library datasets generated to determine substrate specificity profiles of 300 serine/threonine kinases to develop an explainable Transformer model for kinase-peptide interaction prediction. The model, trained solely on primary sequences, achieved state-of-the-art performance. Its unique multitask learning paradigm built within the model enables predictions on virtually any kinase-peptide pair, including predictions on 139 kinases not used in peptide library screens. Furthermore, we employed explainable machine learning methods to elucidate the model's inner workings. Through analysis of learned embeddings at different training stages, we demonstrate that the model employs a unique strategy of substrate prediction considering both substrate motif patterns and kinase evolutionary features. SHapley Additive exPlanation (SHAP) analysis reveals key specificity determining residues in the peptide sequence. Finally, we provide a web interface for predicting kinase-substrate associations for user-defined sequences and a resource for visualizing the learned kinase-substrate associations. AVAILABILITY AND IMPLEMENTATION: All code and data are available at https://github.com/esbgkannan/Phosformer-ST. Web server is available at https://phosformer.netlify.app.

Base-Resolution Sequencing Methods for Whole-Transcriptome Quantification of mRNA Modifications.

ConspectusRNA molecules are not merely a combination of four bases of A, C, G, and U. Chemical modifications occur in almost all RNA species and play diverse roles in gene expression regulation. The abundant cellular RNAs, such as ribosomal RNA (rRNA) and transfer RNA (tRNA), are known to have the highest density of RNA modifications, which exert critical functions in rRNA and tRNA biogenesis, stability, and subsequent translation. In recent years, modifications on low-abundance RNA species in mammalian cells, such as messenger RNA (mRNA), regulatory noncoding RNA (ncRNA), and chromatin-associated RNA (caRNA), have been shown to contain multiple different chemical modifications with functional significance.As the most abundant mRNA modification in mammals, N6-methyladenosine (m6A) affects nearly every stage of mRNA processing and metabolism, with the antibody-based m6A-MeRIP-seq (methylated RNA immunoprecipitation sequencing) followed by high-throughput sequencing widely employed in mapping m6A distribution transcriptome-wide in diverse biological systems. In addition to m6A, other chemical modifications such as pseudouridine (Ψ), 2'-O-methylation (Nm), 5-methylcytidine (m5C), internal N7-methylguanosine (m7G), N1-methyladenosine (m1A), N4-acetylcytidine (ac4C), etc. also exist in polyA-tailed RNA in mammalian cells, requiring effective mapping approaches for whole-transcriptome profiling of these non-m6A mRNA modifications. Like m6A, the antibody-based enrichment followed by sequencing has been the primary method to study distributions of these modifications. Methods to more quantitatively map these modifications would dramatically improve our understanding of distributions and modification density of these chemical marks on RNA, thereby bettering informing functional implications. In this Account, aimed at both single-base resolution and modification fraction quantification, we summarize our recent advances in developing a series of chemistry- or biochemistry-based methods to quantitatively map RNA modifications, including m6A, Ψ, m5C, m1A, 2'-O-methylation (Nm), and internal m7G, in mammalian mRNA at base resolution. These new methods, including m6A-SAC-seq, eTAM-seq, BID-seq, UBS-seq, DAMM-seq, m1A-quant-seq, Nm-Mut-seq, and m7G-quant-seq, promise to conduct base-resolution mapping of most major mRNA modifications with low RNA input and uncover dynamic changes in modification stoichiometry during biological and physiological processes, facilitating future investigations on these RNA modifications in regulating cellular gene expression and as potential biomarkers for clinical diagnosis and prognosis. These quantitative sequencing methods allow the mapping of most mRNA modifications with limited input sample requirements. The same modifications on diverse RNA species, such as caRNA, ncRNA, nuclear nascent RNA, mitochondrial RNA, cell-free RNA (cfRNA), etc., could be sequenced using the same methods.