A vision chip with complementary pathways for open-world sensing.

Image sensors face substantial challenges when dealing with dynamic, diverse and unpredictable scenes in open-world applications. However, the development of image sensors towards high speed, high resolution, large dynamic range and high precision is limited by power and bandwidth. Here we present a complementary sensing paradigm inspired by the human visual system that involves parsing visual information into primitive-based representations and assembling these primitives to form two complementary vision pathways: a cognition-oriented pathway for accurate cognition and an action-oriented pathway for rapid response. To realize this paradigm, a vision chip called Tianmouc is developed, incorporating a hybrid pixel array and a parallel-and-heterogeneous readout architecture. Leveraging the characteristics of the complementary vision pathway, Tianmouc achieves high-speed sensing of up to 10,000 fps, a dynamic range of 130 dB and an advanced figure of merit in terms of spatial resolution, speed and dynamic range. Furthermore, it adaptively reduces bandwidth by 90%. We demonstrate the integration of a Tianmouc chip into an autonomous driving system, showcasing its abilities to enable accurate, fast and robust perception, even in challenging corner cases on open roads. The primitive-based complementary sensing paradigm helps in overcoming fundamental limitations in developing vision systems for diverse open-world applications.

Co-condensation between transcription factor and coactivator p300 modulates transcriptional bursting kinetics.

The coactivator p300/CREB-binding protein (CBP) regulates genes by facilitating the assembly of transcriptional machinery and by acetylating histones and other factors. However, it remains mostly unclear how both functions of p300 are dynamically coordinated during gene control. Here, we showed that p300 can orchestrate two functions through the formation of dynamic clusters with certain transcription factors (TFs), which is mediated by the interactions between a TF's transactivation domain (TAD) and the intrinsically disordered regions of p300. Co-condensation can enable spatially defined, all-or-none activation of p300's catalytic activity, priming the recruitment of coactivators, including Brd4. We showed that co-condensation can modulate transcriptional initiation rate and burst duration of target genes, underlying nonlinear gene regulatory functions. Such modulation is consistent with how p300 might shape gene bursting kinetics globally. Altogether, these results suggest an intriguing gene regulation mechanism, in which TF and p300 co-condensation contributes to transcriptional bursting regulation and cooperative gene control.

Affinity-coupled CCL22 promotes positive selection in germinal centres.

Antibody affinity maturation depends on positive selection in germinal centres (GCs) of rare B cell clones that acquire higher-affinity B cell receptors via somatic hypermutation, present more antigen to follicular helper T (TFH) cells and, consequently, receive more contact-dependent T cell help1. As these GC B cells and TFH cells do not maintain long-lasting contacts in the chaotic GC environment2-4, it is unclear how sufficient T cell help is cumulatively focused onto those rare clones. Here we show that, upon stimulation of CD40, GC B cells upregulate the chemokine CCL22 and to a lesser extent CCL17. By engaging the chemokine receptor CCR4 on TFH cells, CCL22 and CCL17 can attract multiple helper cells from a distance, thus increasing the chance of productive help. During a GC response, B cells that acquire higher antigen-binding affinities express higher levels of CCL22, which in turn 'highlight' these high-affinity GC B cells. Acute increase or blockade of TFH cells helps to rapidly increase or decrease CCL22 expression by GC B cells, respectively. Therefore, a chemokine-based intercellular reaction circuit links the amount of T cell help that individual B cells have received recently to their subsequent ability to attract more help. When CCL22 and CCL17 are ablated in B cells, GCs form but B cells are not affinity-matured efficiently. When competing with wild-type B cells in the same reaction, B cells lacking CCL22 and CCL17 receive less T cell help to maintain GC participation or develop into bone-marrow plasma cells. By uncovering a chemokine-mediated mechanism that highlights affinity-improved B cells for preferential help from TFH cells, our study reveals a principle of spatiotemporal orchestration of GC positive selection.

Dissecting and improving gene regulatory network inference using single-cell transcriptome data.

Single-cell transcriptome data has been widely used to reconstruct gene regulatory networks (GRNs) controlling critical biological processes such as development and differentiation. Although a growing list of algorithms has been developed to infer GRNs using such data, achieving an inference accuracy consistently higher than random guessing has remained challenging. To address this, it is essential to delineate how the accuracy of regulatory inference is limited. Here, we systematically characterized factors limiting the accuracy of inferred GRNs and demonstrated that using pre-mRNA information can help improve regulatory inference compared to the typically used information (i.e., mature mRNA). Using kinetic modeling and simulated single-cell data sets, we showed that target genes' mature mRNA levels often fail to accurately report upstream regulatory activities because of gene-level and network-level factors, which can be improved by using pre-mRNA levels. We tested this finding on public single-cell RNA-seq data sets using intronic reads as proxies of pre-mRNA levels and can indeed achieve a higher inference accuracy compared to using exonic reads (corresponding to mature mRNAs). Using experimental data sets, we further validated findings from the simulated data sets and identified factors such as transcription factor activity dynamics influencing the accuracy of pre-mRNA-based inference. This work delineates the fundamental limitations of gene regulatory inference and helps improve GRN inference using single-cell RNA-seq data.

Proteome characterization of liver-kidney comorbidity after microbial sepsis.

Sepsis is a life-threatening condition that occurs when the body responds to an infection but subsequently triggers widespread inflammation and impaired blood flow. These pathologic responses can rapidly cause multiple organ dysfunction or failure either one by one or simultaneously. The fundamental common mechanisms involved in sepsis-induced multiple organ dysfunction remain unclear. Here, employing quantitative global and phosphoproteomics, we examine the liver's temporal proteome and phosphoproteome changes after moderate sepsis induced by cecum ligation and puncture. In total, 4593 global proteins and 1186 phosphoproteins according to 3275 phosphosites were identified. To characterize the liver-kidney comorbidity after sepsis, we developed a mathematical model and performed cross-analyses of liver and kidney proteome data obtained from the same set of mice. Beyond immune response, we showed the commonly disturbed pathways and key regulators of the liver-kidney comorbidity are linked to energy metabolism and consumption. Our data provide open resources to understand the communication between the liver and kidney as they work to fight infection and maintain homeostasis.

Deciphering a global source of non-genetic heterogeneity in cancer cells.

Cell-to-cell variability within a clonal population, also known as non-genetic heterogeneity, has created significant challenges for intervening with diseases such as cancer. While non-genetic heterogeneity can arise from the variability in the expression of specific genes, it remains largely unclear whether and how clonal cells could be heterogeneous in the expression of the entire transcriptome. Here, we showed that gene transcriptional activity is globally modulated in individual cancer cells, leading to non-genetic heterogeneity in the global transcription rate. Such heterogeneity contributes to cell-to-cell variability in transcriptome size and displays both dynamic and static characteristics, with the global transcription rate temporally modulated in a cell-cycle-coupled manner and the time-averaged rate being distinct between cells and heritable across generations. Additional evidence indicated the role of ATP metabolism in this heterogeneity, and suggested its implication in intrinsic cancer drug tolerance. Collectively, our work shed light on the mode, mechanism, and implication of a global but often hidden source of non-genetic heterogeneity.

Genetic adaptation of skin pigmentation in highland Tibetans.

Strong ultraviolet (UV) radiation at high altitude imposes a serious selective pressure, which may induce skin pigmentation adaptation of indigenous populations. We conducted skin pigmentation phenotyping and genome-wide analysis of Tibetans in order to understand the underlying mechanism of adaptation to UV radiation. We observe that Tibetans have darker baseline skin color compared with lowland Han Chinese, as well as an improved tanning ability, suggesting a two-level adaptation to boost their melanin production. A genome-wide search for the responsible genes identifies GNPAT showing strong signals of positive selection in Tibetans. An enhancer mutation (rs75356281) located in GNPAT intron 2 is enriched in Tibetans (58%) but rare in other world populations (0 to 18%). The adaptive allele of rs75356281 is associated with darker skin in Tibetans and, under UVB treatment, it displays higher enhancer activities compared with the wild-type allele in in vitro luciferase assays. Transcriptome analyses of gene-edited cells clearly show that with UVB treatment, the adaptive variant of GNPAT promotes melanin synthesis, likely through the interactions of CAT and ACAA1 in peroxisomes with other pigmentation genes, and they act synergistically, leading to an improved tanning ability in Tibetans for UV protection.

ZnSe/SnSe Heterostructure Incorporated with Selenium/Nitrogen Co-Doped Carbon Nanofiber Skeleton for Sodium-Ion Batteries.

Effective strategies toward building exquisite nanostructures with enhanced structural integrity and improved reaction kinetics will carry forward the practical application of alloy-based materials as anodes in batteries. Herein, a free-standing 3D carbon nanofiber (CNF) skeleton incorporated with heterostructured binary metal selenides (ZnSe/SnSe) nanoboxes is developed for Na-ion storage anodes, which can facilitate Na+ ion migration, improve structure integrity, and enhance the electrochemical reaction kinetics. During the carbonization and selenization process, selenium/nitrogen (Se/N) is co-doped into the 3D CNF skeleton, which can improve the conductivity and wettability of the CNF matrices. More importantly, the ZnSe/SnSe heterostructures and the Se/N co-doping CNFs can have a synergistic interfacial coupling effect and built-in electric field in the heterogeneous interfaces of ZnSe/SnSe hetero-boundaries as well as the interfaces between the CNF matrix and the selenide heterostructures, which can enable fast ion/electron transport and accelerate surface/internal reaction kinetics for Na-ion storage. The ZnSe/SnSe@Se,N-CNFs exhibit superior Na-ion storage performance than the comparative ZnSe/SnSe, ZnSe and SnSe powders, which deliver an excellent rate performance (882.0, 773.6, 695.7, 634.2, and 559.0 mAh g-1 at current rates of 0.1, 0.2, 0.5, 1, and 2 A g-1) and long-life cycling stability of 587.5 mAh g-1 for 3500 cycles at 2 A g-1.

A multiomics analysis of direct interkingdom dynamics between influenza A virus and Streptococcus pneumoniae uncovers host-independent changes to bacterial virulence fitness.

BACKGROUND: For almost a century, it has been recognized that influenza A virus (IAV) infection can promote the development of secondary bacterial infections (SBI) mainly caused by Streptococcus pneumoniae (Spn). Recent observations have shown that IAV is able to directly bind to the surface of Spn. To gain a foundational understanding of how direct IAV-Spn interaction alters bacterial biological fitness we employed combinatorial multiomic and molecular approaches. RESULTS: Here we show IAV significantly remodels the global transcriptome, proteome and phosphoproteome profiles of Spn independently of host effectors. We identified Spn surface proteins that interact with IAV proteins (hemagglutinin, nucleoprotein, and neuraminidase). In addition, IAV was found to directly modulate expression of Spn virulence determinants such as pneumococcal surface protein A, pneumolysin, and factors associated with antimicrobial resistance among many others. Metabolic pathways were significantly altered leading to changes in Spn growth rate. IAV was also found to drive Spn capsule shedding and the release of pneumococcal surface proteins. Released proteins were found to be involved in evasion of innate immune responses and actively reduced human complement hemolytic and opsonizing activity. IAV also led to phosphorylation changes in Spn proteins associated with metabolism and bacterial virulence. Validation of proteomic data showed significant changes in Spn galactose and glucose metabolism. Furthermore, supplementation with galactose rescued bacterial growth and promoted bacterial invasion, while glucose supplementation led to enhanced pneumolysin production and lung cell apoptosis. CONCLUSIONS: Here we demonstrate that IAV can directly modulate Spn biology without the requirement of host effectors and support the notion that inter-kingdom interactions between human viruses and commensal pathobionts can promote bacterial pathogenesis and microbiome dysbiosis.

Central Dogma Goes Digital.

In this issue of Molecular Cell, Tay and colleagues (Albayrak et al., 2016) describe a new technique to digitally quantify the numbers of protein and mRNA in the same mammalian cell, providing a new way to look at the central dogma of molecular biology.

Identification of a combined hypoxia and lactate metabolism prognostic signature in lung adenocarcinoma : Author.

BACKGROUND: In the tumor microenvironment (TME), a bidirectional relationship exists between hypoxia and lactate metabolism, with each component exerting a reciprocal influence on the other, forming an inextricable link. The aim of the present investigation was to develop a prognostic model by amalgamating genes associated with hypoxia and lactate metabolism. This model is intended to serve as a tool for predicting patient outcomes, including survival rates, the status of the immune microenvironment, and responsiveness to therapy in patients with lung adenocarcinoma (LUAD). METHODS: Transcriptomic sequencing data and patient clinical information specific to LUAD were obtained from comprehensive repositories of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A compendium of genes implicated in hypoxia and lactate metabolism was assembled from an array of accessible datasets. Univariate and multivariate Cox regression analyses were employed. Additional investigative procedures, including tumor mutational load (TMB), microsatellite instability (MSI), functional enrichment assessments and the ESTIMATE, CIBERSORT, and TIDE algorithms, were used to evaluate drug sensitivity and predict the efficacy of immune-based therapies. RESULTS: A novel prognostic signature comprising five lactate and hypoxia-related genes (LHRGs), PKFP, SLC2A1, BCAN, CDKN3, and ANLN, was established. This model demonstrated that LUAD patients with elevated LHRG-related risk scores exhibited significantly reduced survival rates. Both univariate and multivariate Cox analyses confirmed that the risk score was a robust prognostic indicator of overall survival. Immunophenotyping revealed increased infiltration of memory CD4 + T cells, dendritic cells and NK cells in patients classified within the high-risk category compared to their low-risk counterparts. Higher probability of mutations in lung adenocarcinoma driver genes in high-risk groups, and the MSI was associated with the risk-score. Functional enrichment analyses indicated a predominance of cell cycle-related pathways in the high-risk group, whereas metabolic pathways were more prevalent in the low-risk group. Moreover, drug sensitivity analyses revealed increased sensitivity to a variety of drugs in the high-risk group, especially inhibitors of the PI3K-AKT, EGFR, and ELK pathways. CONCLUSIONS: This prognostic model integrates lactate metabolism and hypoxia parameters, offering predictive insights regarding survival, immune cell infiltration and functionality, as well as therapeutic responsiveness in LUAD patients. This model may facilitate personalized treatment strategies, tailoring interventions to the unique molecular profile of each patient's disease.

Influenza Causes MLKL-Driven Cardiac Proteome Remodeling During Convalescence.

RATIONALE: Patients with and without cardiovascular diseases have been shown to be at risk of influenza-mediated cardiac complications. Recent clinical reports support the notion of a direct link between laboratory-confirmed influenza virus infections and adverse cardiac events. OBJECTIVE: Define the molecular mechanisms underlying influenza virus-induced cardiac pathogenesis after resolution of pulmonary infection and the role of necroptosis in this process. METHODS AND RESULTS: Hearts from wild-type and necroptosis-deficient (MLKL [mixed lineage kinase domain-like protein]-KO) mice were dissected 12 days after initial influenza A virus (IAV) infection when viral titers were undetectable in the lungs. Immunofluorescence microscopy and plaque assays showed presence of viable IAV particles in the myocardium without generation of interferon responses. Global proteome and phosphoproteome analyses using high-resolution accurate mass-based LC-MS/MS and label-free quantitation showed that the global proteome as well as the phosphoproteome profiles were significantly altered in IAV-infected mouse hearts in a strain-independent manner. Necroptosis-deficient mice had increased survival and reduced weight loss post-IAV infection, as well as increased antioxidant and mitochondrial function, indicating partial protection to IAV infection. These findings were confirmed in vitro by pretreatment of human and rat myocytes with antioxidants or necroptosis inhibitors, which blunted oxidative stress and mitochondrial damage after IAV infection. CONCLUSIONS: This study provides the first evidence that the cardiac proteome and phosphoproteome are significantly altered post-pulmonary influenza infection. Moreover, viral particles can persist in the heart after lung clearance, altering mitochondrial function and promoting cell death without active replication and interferon responses. Finally, our findings show inhibition of necroptosis or prevention of mitochondrial damage as possible therapeutic interventions to reduce cardiac damage during influenza infections. Graphic Abstract: A graphic abstract is available for this article.

Profiling transcription factor activity dynamics using intronic reads in time-series transcriptome data.

Activities of transcription factors (TFs) are temporally modulated to regulate dynamic cellular processes, including development, homeostasis, and disease. Recent developments of bioinformatic tools have enabled the analysis of TF activities using transcriptome data. However, because these methods typically use exon-based target expression levels, the estimated TF activities have limited temporal accuracy. To address this, we proposed a TF activity measure based on intron-level information in time-series RNA-seq data, and implemented it to decode the temporal control of TF activities during dynamic processes. We showed that TF activities inferred from intronic reads can better recapitulate instantaneous TF activities compared to the exon-based measure. By analyzing public and our own time-series transcriptome data, we found that intron-based TF activities improve the characterization of temporal phasing of cycling TFs during circadian rhythm, and facilitate the discovery of two temporally opposing TF modules during T cell activation. Collectively, we anticipate that the proposed approach would be broadly applicable for decoding global transcriptional architecture during dynamic processes.

Synthesis of Upper-Rim Sulfanylpropyl- and p-Methoxyphenylazo-Substituted Calix[4]arenes as Chromogenic Sensors for Hg2+ and Ag+ Ions.

A series of calix[4]arenes with upper-rim sulfanylpropyl and p-methoxyphenylazo groups (compounds 8-10) were synthesized and found to be effective chromogenic sensors for selectively detecting Hg2+, Hg+, and Ag+ ions among 18 screened metal perchlorates. In comparison to previously reported diallyl- and dithioacetoxypropyl-substituted calix[4]arenes (5, 6, 14, 15, and 16) and the newly synthesized compound 7, the distal (5,17)-disulfanylpropyl-substituted di-p-methoxyphenylazocalix[4]arene 9 demonstrated superior performance with a limit of detection of 0.028 µM for Hg2+ ions in a chloroform/methanol (v/v = 399/1) cosolvent. Job's plot revealed 1:1 binding stoichiometry for all these upper-rim sulfanylpropyl- and p-methoxyphenylazo-substituted calix[4]arenes 8-10 with Hg2+ ions, and Benesi-Hildebrand plots from ultraviolet/visible (UV-vis) titration spectra were used for the determination of their association constants. Our findings indicated that the distal orientation of two p-methoxyphenylazo and two sulfanylpropyl groups in calix[4]arenes 8-10 is more favorable for binding Hg2+ ions than the proximal (5,11-) orientation; moreover, the adjacent sulfanylpropyl groups exhibited superior coordination as ligands compared to the allyl and thioacetoxypropyl groups. Notably, compounds 8-10 displayed a comparable trend in their association with Ag+ ions, albeit with 1 order of magnitude lower binding constants and a distinct binding mode compared to Hg2+ ions. UV-vis spectroscopy, Job's plots, high-resolution mass spectrometry, and 1H nuclear magnetic resonance titration studies are presented and discussed.

TFH cells in bystander and cognate interactions with B cells.

Follicular T-helper (TFH ) cells play a crucial role in three aspects of the germinal center (GC) response. They promote GC formation, arbitrate competition among GC B cells to determine the outcome of affinity maturation, and regulate GC output of memory and plasma cells to shape the long-lived humoral immune memory. Of fundamental importance are dynamic physical interactions between TFH and B cells, which are the main platform for TFH cells to deliver "help" factors to B cells and also for reciprocal signaling from B cells to maintain the helper state of TFH cells. Recent work has significantly expanded our understanding of how T-B interactions are spatiotemporally regulated and molecularly orchestrated to fulfill those TFH functions. In this review, we elaborate two modes of T-B interactions, the antigen-specific or cognate mode in which TFH cells engage individual antigen-presenting B cells and the antigen nonspecific bystander mode in which TFH cells are engaged with the ensemble of follicular B cells. We discuss findings that indicate how short-lived cognate T-B contacts coupled with an intercellular positive feedback drive affinity-based selection and how bystander interactions between T and B cells regulate follicular T-cell recruitment and maintenance of an appropriate helper state. We argue that this combination of bystander and cognate interactions with B cells constantly shapes the internal state of TFH cells and provides the platform to execute their helper functions.

Homologous and heterologous serological response to the N-terminal domain of SARS-CoV-2 in humans and mice.

The increasing numbers of infected cases of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses serious threats to public health and the global economy. Most SARS-CoV-2 neutralizing antibodies target the receptor binding domain (RBD) and some the N-terminal domain (NTD) of the spike protein, which is the major antigen of SARS-CoV-2. While the antibody response to RBD has been extensively characterized, the antigenicity and immunogenicity of the NTD protein are less well studied. Using 227 plasma samples from COVID-19 patients, we showed that SARS-CoV-2 NTD-specific antibodies could be induced during infection. As compared to the results of SARS-CoV-2 RBD, the serological response of SARS-CoV-2 NTD is less cross-reactive with SARS-CoV, a pandemic strain that was identified in 2003. Furthermore, neutralizing antibodies are rarely elicited in a mice model when NTD is used as an immunogen. We subsequently demonstrate that NTD has an altered antigenicity when expressed alone. Overall, our results suggest that while NTD offers a supplementary strategy for serology testing, it may not be suitable as an immunogen for vaccine development.

Kinetic Multi-omic Analysis of Responses to SARS-CoV-2 Infection in a Model of Severe COVID-19.

The host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is poorly understood due to a lack of an animal model that recapitulates severe human disease. Here, we report a Syrian hamster model that develops progressive lethal pulmonary disease that closely mimics severe coronavirus disease 2019 (COVID-19). We evaluated host responses using a multi-omic, multiorgan approach to define proteome, phosphoproteome, and transcriptome changes. These data revealed both type I and type II interferon-stimulated gene and protein expression along with a progressive increase in chemokines, monocytes, and neutrophil-associated molecules throughout the course of infection that peaked in the later time points correlating with a rapidly developing diffuse alveolar destruction and pneumonia that persisted in the absence of active viral infection. Extrapulmonary proteome and phosphoproteome remodeling was detected in the heart and kidneys following viral infection. Together, our results provide a kinetic overview of multiorgan host responses to severe SARS-CoV-2 infection in vivo. IMPORTANCE The current pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has created an urgent need to understand the pathogenesis of this infection. These efforts have been impaired by the lack of animal models that recapitulate severe coronavirus disease 2019 (COVID-19). Here, we report a hamster model that develops severe COVID-19-like disease following infection with human isolates of SARS-CoV-2. To better understand pathogenesis, we evaluated changes in gene transcription and protein expression over the course of infection to provide an integrated multiorgan kinetic analysis of the host response to infection. These data reveal a dynamic innate immune response to infection and corresponding immune pathologies consistent with severe human disease. Altogether, this model will be useful for understanding the pathogenesis of severe COVID-19 and for testing interventions.

Structural insight into the membrane targeting domain of the Legionella deAMPylase SidD.

AMPylation, the post-translational modification with adenosine monophosphate (AMP), is catalyzed by effector proteins from a variety of pathogens. Legionella pneumophila is thus far the only known pathogen that, in addition to encoding an AMPylase (SidM/DrrA), also encodes a deAMPylase, called SidD, that reverses SidM-mediated AMPylation of the vesicle transport GTPase Rab1. DeAMPylation is catalyzed by the N-terminal phosphatase-like domain of SidD. Here, we determined the crystal structure of full length SidD including the uncharacterized C-terminal domain (CTD). A flexible loop rich in aromatic residues within the CTD was required to target SidD to model membranes in vitro and to the Golgi apparatus within mammalian cells. Deletion of the loop (Δloop) or substitution of its aromatic phenylalanine residues rendered SidD cytosolic, showing that the hydrophobic loop is the primary membrane-targeting determinant of SidD. Notably, deletion of the two terminal alpha helices resulted in a CTD variant incapable of discriminating between membranes of different composition. Moreover, a L. pneumophila strain producing SidDΔloop phenocopied a L. pneumophila ΔsidD strain during growth in mouse macrophages and displayed prolonged co-localization of AMPylated Rab1 with LCVs, thus revealing that membrane targeting of SidD via its CTD is a critical prerequisite for its ability to catalyze Rab1 deAMPylation during L. pneumophila infection.

Global Proteome and Phosphoproteome Characterization of Sepsis-induced Kidney Injury.

Sepsis-induced acute kidney injury (S-AKI) is the most common complication in hospitalized and critically ill patients, highlighted by a rapid decline of kidney function occurring a few hours or days after sepsis onset. Systemic inflammation elicited by microbial infections is believed to lead to kidney damage under immunocompromised conditions. However, although AKI has been recognized as a disease with long-term sequelae, partly because of the associated higher risk of chronic kidney disease (CKD), the understanding of kidney pathophysiology at the molecular level and the global view of dynamic regulations in situ after S-AKI, including the transition to CKD, remains limited. Existing studies of S-AKI mainly focus on deriving sepsis biomarkers from body fluids. In the present study, we constructed a mid-severity septic murine model using cecal ligation and puncture (CLP), and examined the temporal changes to the kidney proteome and phosphoproteome at day 2 and day 7 after CLP surgery, corresponding to S-AKI and the transition to CKD, respectively, by employing an ultrafast and economical filter-based sample processing method combined with the label-free quantitation approach. Collectively, we identified 2,119 proteins and 2950 phosphosites through multi-proteomics analyses. Among them, we identified an array of highly promising candidate marker proteins indicative of disease onset and progression accompanied by immunoblot validations, and further denoted the pathways that are specifically responsive to S-AKI and its transition to CKD, which include regulation of cell metabolism regulation, oxidative stress, and energy consumption in the diseased kidneys. Our data can serve as an enriched resource for the identification of mechanisms and biomarkers for sepsis-induced kidney diseases.