Rp3: Ribosome profiling-assisted proteogenomics improves coverage and confidence during microprotein discovery.

There has been a dramatic increase in the identification of non-canonical translation and a significant expansion of the protein-coding genome. Among the strategies used to identify unannotated small Open Reading Frames (smORFs) that encode microproteins, Ribosome profiling (Ribo-Seq) is the gold standard for the annotation of novel coding sequences by reporting on smORF translation. In Ribo-Seq, ribosome-protected footprints (RPFs) that map to multiple genomic sites are removed since they cannot be unambiguously assigned to a specific genomic location. Furthermore, RPFs necessarily result in short (25-34 nucleotides) reads, increasing the chance of multi-mapping alignments, such that smORFs residing in these regions cannot be identified by Ribo-Seq. Moreover, it has been challenging to identify protein evidence for Ribo-Seq. To solve this, we developed Rp3, a pipeline that integrates proteogenomics and Ribosome profiling to provide unambiguous evidence for a subset of microproteins missed by current Ribo-Seq pipelines. Here, we show that Rp3 maximizes proteomics detection and confidence of microprotein-encoding smORFs.

SEraster: a rasterization preprocessing framework for scalable spatial omics data analysis.

MOTIVATION: Spatial omics data demand computational analysis but many analysis tools have computational resource requirements that increase with the number of cells analyzed. This presents scalability challenges as researchers use spatial omics technologies to profile millions of cells. RESULTS: To enhance the scalability of spatial omics data analysis, we developed a rasterization preprocessing framework called SEraster that aggregates cellular information into spatial pixels. We apply SEraster to both real and simulated spatial omics data prior to spatial variable gene expression analysis to demonstrate that such preprocessing can reduce computational resource requirements while maintaining high performance, including as compared to other down-sampling approaches. We further integrate SEraster with existing analysis tools to characterize cell-type spatial co-enrichment across length scales. Finally, we apply SEraster to enable analysis of a mouse pup spatial omics dataset with over a million cells to identify tissue-level and cell-type-specific spatially variable genes as well as spatially co-enriched cell types that recapitulate expected organ structures. AVAILABILITY AND IMPLEMENTATION: SEraster is implemented as an R package on GitHub (https://github.com/JEFworks-Lab/SEraster) with additional tutorials at https://JEF.works/SEraster.

Profiling ephedrine/pseudoephedrine and methamphetamine synthesised from benzaldehyde, nitroethane and dimethyl carbonate.

In previous work, a novel pathway for the synthesis of ephedrine/pseudoephedrine and methamphetamine using the precursors benzaldehyde, nitroethane and dimethyl carbonate was investigated, and an impurity profile presented. This paper presents chiral and stable isotope ratios of ephedrine/pseudoephedrine and methamphetamine synthesised by this pathway. Based on the chiral profile and the more negative δ13C (avg. -33.2‰) and more positive δ2H values, it is possible to distinguish ephedrine/pseudoephedrine and methamphetamine prepared from this pathway from those of "fully synthetic", "semi-synthetic" or "natural" origin. The more positive δ2H values of methamphetamine from this pathway allowed for differentiation from methamphetamine produced from phenyl-2-propanone. It was noted, however, that the use of stable isotope profiling would likely be limited when a benzaldehyde source having a negative δ2H value was used as a precursor. Furthermore, the stable isotope values alone could not be used to differentiate from methamphetamine prepared by the Akabori-Momotani reaction, highlighting the need for combination with impurity profiling.

Humanin variant P3S is associated with longevity in APOE4 carriers and resists APOE4-induced brain pathology.

The APOE4 allele is recognized as a significant genetic risk factor to Alzheimer's disease (AD) and influences longevity. Nonetheless, some APOE4 carriers exhibit resistance to AD even in advanced age. Humanin, a mitochondrial-derived peptide comprising 24 amino acids, has variants linked to cognitive resilience and longevity. Our research uncovered a unique humanin variant, P3S, specifically enriched in centenarians with the APOE4 allele. Through in silico analyses and subsequent experimental validation, we demonstrated a strong affinity between humanin P3S and APOE4. Utilizing an APOE4-centric mouse model of amyloidosis (APP/PS1/APOE4), we observed that humanin P3S significantly attenuated brain amyloid-beta accumulation compared to the wild-type humanin. Transcriptomic assessments of mice treated with humanin P3S highlighted its potential mechanism involving the enhancement of amyloid beta phagocytosis. Additionally, in vitro studies corroborated humanin P3S's efficacy in promoting amyloid-beta clearance. Notably, in the temporal cortex of APOE4 carriers, humanin expression is correlated with genes associated with phagocytosis. Our findings suggest a role of the rare humanin variant P3S, especially prevalent among individuals of Ashkenazi descent, in mitigating amyloid beta pathology and facilitating phagocytosis in APOE4-linked amyloidosis, underscoring its significance in longevity and cognitive health among APOE4 carriers.

Mitochondrial-derived microprotein MOTS-c attenuates immobilization-induced skeletal muscle atrophy by suppressing lipid infiltration.

Mitochondrial open reading frame of the 12S ribosomal RNA type-c (MOTS-c), a mitochondrial microprotein, has been described as a novel regulator of glucose and lipid metabolism. In addition to its role as a metabolic regulator, MOTS-c prevents skeletal muscle atrophy in high fat-fed mice. Here, we examined the preventive effect of MOTS-c on skeletal muscle mass, using an immobilization-induced muscle atrophy model, and explored its underlying mechanisms. Male C57BL/6J mice (10 wk old) were randomly assigned to one of the three experimental groups: nonimmobilization control group (sterilized water injection), immobilization control group (sterilized water injection), and immobilization and MOTS-c-treated group (15 mg/kg/day MOTS-c injection). We used casting tape for the immobilization experiment. After 8 days of the experimental period, skeletal muscle samples were collected and used for Western blotting, RNA sequencing, and lipid and collagen assays. Immobilization reduced ∼15% of muscle mass, whereas MOTS-c treatment attenuated muscle loss, with only a 5% reduction. MOTS-c treatment also normalized phospho-AKT, phospho-FOXO1, and phospho-FOXO3a expression levels and reduced circulating inflammatory cytokines, such as interleukin-1b (IL-1ß), interleukin-6 (IL-6), chemokine C-X-C motif ligand 1 (CXCL1), and monocyte chemoattractant protein 1 (MCP-1), in immobilized mice. Unbiased RNA sequencing and its downstream analyses demonstrated that MOTS-c modified adipogenesis-modulating gene expression within the peroxisome proliferator-activated receptor (PPAR) pathway. Supporting this observation, muscle fatty acid levels were lower in the MOTS-c-treated group than in the casted control mice. These results suggest that MOTS-c treatment inhibits skeletal muscle lipid infiltration by regulating adipogenesis-related genes and prevents immobilization-induced muscle atrophy.NEW & NOTEWORTHY MOTS-c, a mitochondrial microprotein, attenuates immobilization-induced skeletal muscle atrophy. MOTS-c treatment improves systemic inflammation and skeletal muscle AKT/FOXOs signaling pathways. Furthermore, unbiased RNA sequencing and subsequent assays revealed that MOTS-c prevents lipid infiltration in skeletal muscle. Since lipid accumulation is one of the common pathologies among other skeletal muscle atrophies induced by aging, obesity, cancer cachexia, and denervation, MOTS-c treatment could be effective in other muscle atrophy models as well.

A naturally occurring variant of SHLP2 is a protective factor in Parkinson's disease.

Mitochondrial DNA single nucleotide polymorphisms (mtSNPs) have been associated with a reduced risk of developing Parkinson's disease (PD), yet the underlying mechanisms remain elusive. In this study, we investigate the functional role of a PD-associated mtSNP that impacts the mitochondrial-derived peptide (MDP) Small Humanin-like Peptide 2 (SHLP2). We identify m.2158 T > C, a mtSNP associated with reduced PD risk, within the small open reading frame encoding SHLP2. This mtSNP results in an alternative form of SHLP2 (lysine 4 replaced with arginine; K4R). Using targeted mass spectrometry, we detect specific tryptic fragments of SHLP2 in neuronal cells and demonstrate its binding to mitochondrial complex 1. Notably, we observe that the K4R variant, associated with reduced PD risk, exhibits increased stability compared to WT SHLP2. Additionally, both WT and K4R SHLP2 show enhanced protection against mitochondrial dysfunction in in vitro experiments and confer protection against a PD-inducing toxin, a mitochondrial complex 1 inhibitor, in a mouse model. This study sheds light on the functional consequences of the m.2158 T > C mtSNP on SHLP2 and provides insights into the potential mechanisms by which this mtSNP may reduce the risk of PD.

Single cell and spatial transcriptomics analysis of kidney double negative T lymphocytes in normal and ischemic mouse kidneys.

T cells are important in the pathogenesis of acute kidney injury (AKI), and TCR+CD4-CD8- (double negative-DN) are T cells that have regulatory properties. However, there is limited information on DN T cells compared to traditional CD4+ and CD8+ cells. To elucidate the molecular signature and spatial dynamics of DN T cells during AKI, we performed single-cell RNA sequencing (scRNA-seq) on sorted murine DN, CD4+, and CD8+ cells combined with spatial transcriptomic profiling of normal and post AKI mouse kidneys. scRNA-seq revealed distinct transcriptional profiles for DN, CD4+, and CD8+ T cells of mouse kidneys with enrichment of Kcnq5, Klrb1c, Fcer1g, and Klre1 expression in DN T cells compared to CD4+ and CD8+ T cells in normal kidney tissue. We validated the expression of these four genes in mouse kidney DN, CD4+ and CD8+ T cells using RT-PCR and Kcnq5, Klrb1, and Fcer1g genes with the NIH human kidney precision medicine project (KPMP). Spatial transcriptomics in normal and ischemic mouse kidney tissue showed a localized cluster of T cells in the outer medulla expressing DN T cell genes including Fcer1g. These results provide a template for future studies in DN T as well as CD4+ and CD8+ cells in normal and diseased kidneys.

The Integration of Proteogenomics and Ribosome Profiling Circumvents Key Limitations to Increase the Coverage and Confidence of Novel Microproteins.

There has been a dramatic increase in the identification of non-conical translation and a significant expansion of the protein-coding genome and proteome. Among the strategies used to identify novel small ORFs (smORFs), Ribosome profiling (Ribo-Seq) is the gold standard for the annotation of novel coding sequences by reporting on smORF translation. In Ribo-Seq, ribosome-protected footprints (RPFs) that map to multiple sites in the genome are computationally removed since they cannot unambiguously be assigned to a specific genomic location, or to a specific transcript in the case of multiple isoforms. Furthermore, RPFs necessarily result in short (25-34 nucleotides) reads, increasing the chance of ambiguous and multi-mapping alignments, such that smORFs that reside in these regions cannot be identified by Ribo-Seq. Here, we show that the inclusion of proteogenomics to create a Ribosome Profiling and Proteogenomics Pipeline (RP3) bypasses this limitation to identify a group of microprotein-encoding smORFs that are missed by current Ribo-Seq pipelines. Moreover, we show that the microproteins identified by RP3 have different sequence compositions from the ones identified by Ribo-Seq-only pipelines, which can affect proteomics identification. In aggregate, the development of RP3 maximizes the detection and confidence of protein-encoding smORFs and microproteins.

Evaluating Stacked Methylation Markers for Blood-Based Multicancer Detection.

The ability to detect several types of cancer using a non-invasive, blood-based test holds the potential to revolutionize oncology screening. We mined tumor methylation array data from the Cancer Genome Atlas (TCGA) covering 14 cancer types and identified two novel, broadly-occurring methylation markers at TLX1 and GALR1. To evaluate their performance as a generalized blood-based screening approach, along with our previously reported methylation biomarker, ZNF154, we rigorously assessed each marker individually or combined. Utilizing TCGA methylation data and applying logistic regression models within each individual cancer type, we found that the three-marker combination significantly increased the average area under the ROC curve (AUC) across the 14 tumor types compared to single markers (p = 1.158 × 10-10; Friedman test). Furthermore, we simulated dilutions of tumor DNA into healthy blood cell DNA and demonstrated increased AUC of combined markers across all dilution levels. Finally, we evaluated assay performance in bisulfite sequenced DNA from patient tumors and plasma, including early-stage samples. When combining all three markers, the assay correctly identified nine out of nine lung cancer plasma samples. In patient plasma from hepatocellular carcinoma, ZNF154 alone yielded the highest combined sensitivity and specificity values averaging 68% and 72%, whereas multiple markers could achieve higher sensitivity or specificity, but not both. Altogether, this study presents a comprehensive pipeline for the identification, testing, and validation of multi-cancer methylation biomarkers with a considerable potential for detecting a broad range of cancer types in patient blood samples.

Novel Insights into Mitochondrial DNA: Mitochondrial Microproteins and mtDNA Variants Modulate Athletic Performance and Age-Related Diseases.

Sports genetics research began in the late 1990s and over 200 variants have been reported as athletic performance- and sports injuries-related genetic polymorphisms. Genetic polymorphisms in the α-actinin-3 (ACTN3) and angiotensin-converting enzyme (ACE) genes are well-established for athletic performance, while collagen-, inflammation-, and estrogen-related genetic polymorphisms are reported as genetic markers for sports injuries. Although the Human Genome Project was completed in the early 2000s, recent studies have discovered previously unannotated microproteins encoded in small open reading frames. Mitochondrial microproteins (also called mitochondrial-derived peptides) are encoded in the mtDNA, and ten mitochondrial microproteins, such as humanin, MOTS-c (mitochondrial ORF of the 12S rRNA type-c), SHLPs 1-6 (small humanin-like peptides 1 to 6), SHMOOSE (Small Human Mitochondrial ORF Over SErine tRNA), and Gau (gene antisense ubiquitous in mtDNAs) have been identified to date. Some of those microproteins have crucial roles in human biology by regulating mitochondrial function, and those, including those to be discovered in the future, could contribute to a better understanding of human biology. This review describes a basic concept of mitochondrial microproteins and discusses recent findings about the potential roles of mitochondrial microproteins in athletic performance as well as age-related diseases.

Mitochondrial DNA variation in Alzheimer's disease reveals a unique microprotein called SHMOOSE.

Mitochondrial DNA variants have previously associated with disease, but the underlying mechanisms have been largely elusive. Here, we report that mitochondrial SNP rs2853499 associated with Alzheimer's disease (AD), neuroimaging, and transcriptomics. We mapped rs2853499 to a novel mitochondrial small open reading frame called SHMOOSE with microprotein encoding potential. Indeed, we detected two unique SHMOOSE-derived peptide fragments in mitochondria by using mass spectrometry-the first unique mass spectrometry-based detection of a mitochondrial-encoded microprotein to date. Furthermore, cerebrospinal fluid (CSF) SHMOOSE levels in humans correlated with age, CSF tau, and brain white matter volume. We followed up on these genetic and biochemical findings by carrying out a series of functional experiments. SHMOOSE acted on the brain following intracerebroventricular administration, differentiated mitochondrial gene expression in multiple models, localized to mitochondria, bound the inner mitochondrial membrane protein mitofilin, and boosted mitochondrial oxygen consumption. Altogether, SHMOOSE has vast implications for the fields of neurobiology, Alzheimer's disease, and microproteins.

Racial differences in circulating mitochondria-derived peptides may contribute to prostate cancer health disparities.

INTRODUCTION: The mitochondrial genome has small open reading frames (sORF) which produce measurable mitochondrial-derived peptides (MDPs), including humanin, SHLP2, and MOTS-c. Previously, among men undergoing prostate biopsy, we found higher serum SHLP2 was linked with lower prostate cancer (PC) risk in European American men (EAM), while null associations were found in African American men (AAM). Here, in different patients undergoing prostate biopsy, we tested the link between SHLP2, humanin and MOTS-c and PC risk by race. METHODS: Plasma SHLP2, humanin, and MOTS-c were measured in 198 men (50/49 EAM/AAM cases; 50/49 EAM/AAM controls) undergoing biopsy. Logistic and multinomial regression models tested associations between each MDP and PC diagnosis, low-grade (grade group, GG1) and high-grade (GG2-5). Models were adjusted for age, body mass index, digital rectal examination, and prostate specific antigen (PSA). We tested interactions between MDPs and race. RESULTS: Among controls, humanin was similar by race (p = 0.60), but both SHLP2 (p = 0.007) and MOTS-c (p = 0.026) were lower in AAM controls versus EAM controls. Among EAM, higher MDP values were associated with lower PC risk (all p ≤ 0.001), with null associations in AAM (all p-interactions ≤ 0.01). Similarly, higher MDP expression was associated with decreased risk of low- and high-grade PC in EAM (all p ≤ 0.005) with null associations in AAM. CONCLUSIONS: Higher MDP levels were associated with lower PC risk in EAM but not AAM. Generally, AAM controls had lower MDP levels. These data support MDPs and mitochondrial dysfunction in PC, suggesting greater dysfunction in AAM may contribute to excess PC risk. Future larger studies are needed to confirm these results.

Sports activities at a young age decrease hypertension risk-The J-Fit+ study.

This study aimed to assess (1) blood pressure between young, current athletes, and non-athletes early in life; (2) hypertension prevalence between former athletes and the general population later in life; and (3) understand the mechanisms between exercise training and hypertension risks in the form of DNA methylation. Study 1: A total of 354 young male participants, including current athletes, underwent blood pressure assessment. Study 2: The prevalence of hypertension in 1269 male former athletes was compared with that in the Japanese general population. Current and former athletes were divided into three groups: endurance-, mixed-, and sprint/power-group. Study 3: We analyzed the effect of aerobic- or resistance-training on DNA methylation patterns using publicly available datasets to explore the possible underlying mechanisms. In young, current athletes, the mixed- and sprint/power-group exhibited higher systolic blood pressure, and all groups exhibited higher pulse pressure than non-athletes. In contrast, the prevalence of hypertension in former athletes was significantly lower in all groups than in the general population. Compared to endurance-group (reference), adjusted-hazard ratios for the incidence of hypertension among mixed- and sprint/power-group were 1.24 (0.87-1.84) and 1.50 (1.04-2.23), respectively. Moreover, aerobic- and resistance-training commonly modified over 3000 DNA methylation sites in skeletal muscle, and these were suggested to be associated with cardiovascular function-related pathways. These findings suggest that the high blood pressure induced by exercise training at a young age does not influence the development of future hypertension. Furthermore, previous exercise training experiences at a young age could decrease the risk of future hypertension.

Mitochondria-derived peptides in aging and healthspan.

The mechanisms that explain mitochondrial dysfunction in aging and healthspan continue to be studied, but one element has been unexplored: microproteins. Small open reading frames in circular mitochondria DNA can encode multiple microproteins, called mitochondria-derived peptides (MDPs). Currently, eight MDPs have been published: humanin, MOTS-c, and SHLPs 1-6. This Review describes recent advances in microprotein discovery with a focus on MDPs. It discusses what is currently known about MDPs in aging and how this new understanding could add to the way we understand age-related diseases including type 2 diabetes, cancer, and neurodegenerative diseases at the genomic, proteomic, and drug-development levels.

Weed Warden: A low-cost weed detection device implemented with spectral triad sensor for agricultural applications.

Controlling weeds is essential for farmers to protect resources and maximize crop yield. Between crops, weeds are typically controlled by applying herbicides or tillage to the entire field. However, these control methods are expensive and can pose environmental risks. Robotic weeding systems are a good solution to minimize environmental impact and save money on herbicides, but they are expensive (>$100,000). The Weed Warden is a low-cost (<$200) plant detection sensor that can be mounted on rovers or tractors. The Weed Warden uses an open source multispectral sensor to detect live vegetation and sends a logic signal that could trigger a weed removal system such as a sprayer or mechanical tillage when vegetation is detected. We evaluate the Normalized Difference Vegetation Index (NDVI), Enhanced Normalized Difference Vegetation Index (ENDVI), and Enhanced Vegetation Index (EVI), for producing a value that, combined with a calibrated threshold, will indicate if there is plant life under the sensor. The Weed Warden system using ENDVI is most consistent at detection, with the ability to discriminate 7.6x7.6 cm vegetation samples from bare soil at sensor heights of 30 and 41 cm from the ground. The Weed Warden is a proof-of-concept component of an alternative system to robotic weeders of fallow fields that could help reduce costs, improve environmental outcomes in agricultural settings, and advance research into fallow field management practices.

Reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data.

Recent technological advancements have enabled spatially resolved transcriptomic profiling but at multi-cellular pixel resolution, thereby hindering the identification of cell-type-specific spatial patterns and gene expression variation. To address this challenge, we develop STdeconvolve as a reference-free approach to deconvolve underlying cell types comprising such multi-cellular pixel resolution spatial transcriptomics (ST) datasets. Using simulated as well as real ST datasets from diverse spatial transcriptomics technologies comprising a variety of spatial resolutions such as Spatial Transcriptomics, 10X Visium, DBiT-seq, and Slide-seq, we show that STdeconvolve can effectively recover cell-type transcriptional profiles and their proportional representation within pixels without reliance on external single-cell transcriptomics references. STdeconvolve provides comparable performance to existing reference-based methods when suitable single-cell references are available, as well as potentially superior performance when suitable single-cell references are not available. STdeconvolve is available as an open-source R software package with the source code available at https://github.com/JEFworks-Lab/STdeconvolve .

Humanin-induced autophagy plays important roles in skeletal muscle function and lifespan extension.

BACKGROUND: Autophagy, a highly conserved homeostatic mechanism, is essential for cell survival. The decline of autophagy function has been implicated in various diseases as well as aging. Although mitochondria play a key role in the autophagy process, whether mitochondrial-derived peptides are involved in this process has not been explored. METHODS: We developed a high through put screening method to identify potential autophagy inducers among mitochondrial-derived peptides. We used three different cell lines, mice, c.elegans, and a human cohort to validate the observation. RESULTS: Humanin, a mitochondrial-derived peptide, increases autophagy and maintains autophagy flux in several cell types. Humanin administration increases the expression of autophagy-related genes and lowers accumulation of harmful misfolded proteins in mice skeletal muscle, suggesting that humanin-induced autophagy potentially contributes to the improved skeletal function. Moreover, autophagy is a critical role in humanin-induced lifespan extension in C. elegans. CONCLUSIONS: Humanin is an autophagy inducer. GENERAL SIGNIFICANCE: This paper presents a significant, novel discovery regarding the role of the mitochondrial derived peptide humanin in autophagy regulation and as a possible therapeutic target for autophagy in various age-related diseases.

The MOTS-c K14Q polymorphism in the mtDNA is associated with muscle fiber composition and muscular performance.

Human skeletal muscle fiber is heterogenous due to its diversity of slow- and fast-twitch fibers. In human, slow-twitched fiber gene expression is correlated to MOTS-c, a mitochondria-derived peptide that has been characterized as an exercise mimetic. Within the MOTS-c open reading frame, there is an East Asian-specific m.1382A>C polymorphism (rs111033358) that changes the 14th amino acid of MOTS-c (i.e., K14Q), a variant of MOTS-c that has less biological activity. Here, we examined the influence of the m.1382A>C polymorphism causing MOTS-c K14Q on skeletal muscle fiber composition and physical performance. The myosin heavy chain (MHC) isoforms (MHC-I, MHC-IIa, and MHC-IIx) as an indicator of muscle fiber composition were assessed in 211 Japanese healthy individuals (102 men and 109 women). Muscular strength was measured in 86 physically active young Japanese men by using an isokinetic dynamometer. The allele frequency of the m.1382A>C polymorphism was assessed in 721 Japanese athletes and 873 ethnicity-matched controls. The m.1382A>C polymorphism genotype was analyzed by TaqMan SNP Genotyping Assay. Individuals with the C allele of the m.1382A>C exhibited a higher proportion of MHC-IIx, an index of fast-twitched fiber, than the A allele carriers. Men with the C allele of m.1382A>C exhibited significantly higher peak torques of leg flexion and extension. Furthermore, the C allele frequency was higher in the order of sprint/power athletes (6.5%), controls (5.1%), and endurance athletes (2.9%). Additionally, young male mice were injected with the MOTS-c neutralizing antibody once a week for four weeks to mimic the C allele of the m.1382A>C and assessed for protein expression levels of MHC-fast and MHC-slow. Mice injected with MOTS-c neutralizing antibody showed a higher expression of MHC-fast than the control mice. These results suggest that the C allele of the East Asian-specific m.1382A>C polymorphism leads to the MOTS-c K14Q contributes to the sprint/power performance through regulating skeletal muscle fiber composition.

Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities.

Recent technological advances have enabled spatially resolved measurements of expression profiles for hundreds to thousands of genes in fixed tissues at single-cell resolution. However, scalable computational analysis methods able to take into consideration the inherent 3D spatial organization of cell types and nonuniform cellular densities within tissues are still lacking. To address this, we developed MERINGUE, a computational framework based on spatial autocorrelation and cross-correlation analysis to identify genes with spatially heterogeneous expression patterns, infer putative cell-cell communication, and perform spatially informed cell clustering in 2D and 3D in a density-agnostic manner using spatially resolved transcriptomic data. We applied MERINGUE to a variety of spatially resolved transcriptomic data sets including multiplexed error-robust fluorescence in situ hybridization (MERFISH), spatial transcriptomics, Slide-seq, and aligned in situ hybridization (ISH) data. We anticipate that such statistical analysis of spatially resolved transcriptomic data will facilitate our understanding of the interplay between cell state and spatial organization in tissue development and disease.