A better index for analysis of co-occurrence and similarity

Are you with me? Co-occurrence tests from community ecology can identify positive and negative epistasis between inversions in Mimulus guttatus

Chromosomal inversions are structural genetic variants that can play a crucial role in adaptive evolution and speciation. Patterns of attraction and repulsion among unlinked inversions - whether they tend to be carried by the same or different individuals- can indicate how selection is acting on these polymorphisms. In this study, we compare analytical techniques using data from 64 inversions that segregate among 1373 F2 plants of the yellow monkeyflower Mimulus guttatus. Mendelian assortment provides a strong null hypothesis for [Formula: see text] contingency tests. Here, we show how co-occurrence metrics used in community ecology can provide additional insight regarding coupling and repulsion of inversions at genotypic level. The centered Jaccard/Tanimoto index and the affinity score describe the specific way that inversions interact to generate epistasis for plant survival. We further explore the use of network analysis to visualize inversion interactions and to identify essential third and fourth order interactions, which expand the traditional pairwise scope of the co-occurrence metrics. We suggest that a combination of different statistical approaches will provide the most complete characterization of the fitness effects, both for inversions and other polymorphisms essential to adaptation and speciation.

Late Quaternary fluctuation in upper range limit of trees shapes endemic flora diversity on the Tibetan Plateau

The influence of paleoclimate in shaping current biodiversity pattern is widely acknowledged. However, it remains unclear how the upper paleo-range limit of trees, which dictated the habitat of endemic alpine species, affects the variability in endemic alpine species composition across space over the Tibetan Plateau. We integrated satellite-derived upper range limit of trees, dendrochronological data, and fossil pollen records with a paleoclimate dataset in a climate-driven predictive model to reconstruct the spatio-temporal upper range limit of trees at 100-year intervals since the Last Glacial Maximum. Our results show that trees distributed at the lowest elevations during the Last Glacial Maximum (~3426 m), and ascended to the highest elevations during the Holocene Climatic Optimum (~4187 m), a level ~180 m higher than the present-day (~4009 m). The temporal fluctuations in paleo-range limits of trees play a more important role than paleoclimate in shaping the current spatial pattern of beta-diversity of endemic flora, with regions witnessing higher fluctuations having lower beta-diversity. We therefore suggest that anthropogenic-caused climate change on decadal-to-centennial timescales could lead to higher fluctuations in range limits than orbitally-forced climate variability on centennial-to-millennium timescales, which consequently could cause spatial homogenization of endemic alpine species composition, threatening Tibetan endemic species pool.

CooccurrenceAffinity: An R package for computing a novel metric of affinity in co-occurrence data that corrects for pervasive errors in traditional indices

1. Analysis of co-occurrence data with traditional indices has led to many problems such as sensitivity of the indices to prevalence and the same value representing either a strong positive or strong negative association across different datasets. In our recent study (Mainali et al 2022), we revealed the source of the problems that make the traditional indices fundamentally flawed and unreliable-namely that the indices in common use have no target of estimation quantifying degree of association in the non-null case-and we further developed a novel parameter of association, alpha, with complete formulation of the null distribution for estimating the mechanism of affinity. We also developed the maximum likelihood estimate (MLE) of alpha in our previous study. 2. Here, we introduce the CooccurrenceAffinity R package that computes the MLE for alpha. We provide functions to perform the analysis based on a 2×2 contingency table of occurrence/co-occurrence counts as well as a m×n presence-absence matrix (e.g., species by site matrix). The flexibility of the function allows a user to compute the alpha MLE for entity pairs on matrix columns based on presence-absence states recorded in the matrix rows, or for entity pairs on matrix rows based on presence-absence recorded in columns. We also provide functions for plotting the computed indices. 3. As novel components of this software paper not reported in the original study, we present theoretical discussion of a median interval and of four types of confidence intervals. We further develop functions (a) to compute those intervals, (b) to evaluate their true coverage probability of enclosing the population parameter, and (c) to generate figures. 4. CooccurrenceAffinity is a practical and efficient R package with user-friendly functions for end-to-end analysis and plotting of co-occurrence data in various formats, making it possible to compute the recently developed metric of alpha MLE as well as its median and confidence intervals introduced in this paper. The package supplements its main output of the novel metric of association with the three most common traditional indices of association in co-occurrence data: Jaccard, Sørensen-Dice, and Simpson.

GraCEImpute: A novel graph clustering autoencoder approach for imputation of single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) technology establishes a unique view for elucidating cellular heterogeneity in various biological systems. Yet the scRNA-seq data is compromised by a high dropout rate due to the technological limitation, and the substantial data loss poses computational challenges on subsequent analyses. This study introduces a novel graph clustering autoencoder (GCAE)-based imputation approach (GraCEImpute) to address the challenge of missing data in scRNA-seq data. Our comprehensive evaluation demonstrates that the GraCEImpute model outperforms existing approaches in accurately imputing dropout zeros within scRNA-seq data. The proposed GraCEImpute model also demonstrates the significantly enhanced quality of downstream scRNA-seq data analyses, including clustering, differential gene expression (DEG) analysis, and cell trajectory inference. These improvements underscore the GraCEImpute model's potential to facilitate a deeper understanding of cellular processes and heterogeneity through the scRNA-seq data analyses. The source code is released at https://www.healthinformaticslab.org/supp/.

Forest carbon stocks increase with higher dominance of ectomycorrhizal trees in high latitude forests

Understanding the mechanisms controlling forest carbon accumulation is crucial for predicting and mitigating future climate change. Yet, it remains unclear whether the dominance of ectomycorrhizal (EcM) trees influences the carbon accumulation of entire forests. In this study, we analyzed forest inventory data from over 4000 forest plots across Northeast China. We find that EcM tree dominance consistently exerts a positive effect on tree, soil, and forest carbon stocks. Moreover, we observe that these positive effects are more pronounced during unfavorable climate conditions, at lower tree species richness, and during early successional stages. This underscores the potential of increasing the dominance of native EcM tree species not only to enhance carbon stocks but also to bolster resilience against climate change in high-latitude forests. Here we show that forest managers can make informed decisions to optimize carbon accumulation by considering various factors such as mycorrhizal types, climate, successional stages, and species richness.

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.

Metatranscriptomic investigation of single Ixodes pacificus ticks reveals diverse microbes, viruses, and novel mRNA-like endogenous viral elements

Ticks are increasingly important vectors of human and agricultural diseases. While many studies have focused on tick-borne bacteria, far less is known about tick-associated viruses and their roles in public health or tick physiology. To address this, we investigated patterns of bacterial and viral communities across two field populations of western black-legged ticks (Ixodes pacificus). Through metatranscriptomic analysis of 100 individual ticks, we quantified taxon prevalence, abundance, and co-occurrence with other members of the tick microbiome. In addition to commonly found tick-associated microbes, we assembled 11 novel RNA virus genomes from Rhabdoviridae, Chuviridae, Picornaviridae, Phenuiviridae, Reoviridae, Solemovidiae, Narnaviridae and two highly divergent RNA virus genomes lacking sequence similarity to any known viral families. We experimentally verified the presence of these in I. pacificus ticks across several life stages. We also unexpectedly identified numerous virus-like transcripts that are likely encoded by tick genomic DNA, and which are distinct from known endogenous viral element-mediated immunity pathways in invertebrates. Taken together, our work reveals that I. pacificus ticks carry a greater diversity of viruses than previously appreciated, in some cases resulting in evolutionarily acquired virus-like transcripts. Our findings highlight how pervasive and intimate tick-virus interactions are, with major implications for both the fundamental biology and vectorial capacity of I. pacificus ticks.

IMPORTANCE

Ticks are increasingly important vectors of disease, particularly in the United States where expanding tick ranges and intrusion into previously wild areas has resulted in increasing human exposure to ticks. Emerging human pathogens have been identified in ticks at an increasing rate, and yet little is known about the full community of microbes circulating in various tick species, a crucial first step to understanding how they interact with each and their tick host, as well as their ability to cause disease in humans. We investigated the bacterial and viral communities of the Western blacklegged tick in California and found 11 previously uncharacterized viruses circulating in this population.

The geographic distribution, and the biotic and abiotic predictors of select zoonotic pathogen detections in Canadian polar bears

Increasing Arctic temperatures are facilitating the northward expansion of more southerly hosts, vectors, and pathogens, exposing naïve populations to pathogens not typical at northern latitudes. To understand such rapidly changing host-pathogen dynamics, we need sensitive and robust surveillance tools. Here, we use a novel multiplexed magnetic-capture and droplet digital PCR (ddPCR) tool to assess a sentinel Arctic species, the polar bear (Ursus maritimus; n = 68), for the presence of five zoonotic pathogens (Erysipelothrix rhusiopathiae, Francisella tularensis, Mycobacterium tuberculosis complex, Toxoplasma gondii and Trichinella spp.), and observe associations between pathogen presence and biotic and abiotic predictors. We made two novel detections: the first detection of a Mycobacterium tuberculosis complex member in Arctic wildlife and the first of E. rhusiopathiae in a polar bear. We found a prevalence of 37% for E. rhusiopathiae, 16% for F. tularensis, 29% for Mycobacterium tuberculosis complex, 18% for T. gondii, and 75% for Trichinella spp. We also identify associations with bear age (Trichinella spp.), harvest season (F. tularensis and MTBC), and human settlements (E. rhusiopathiae, F. tularensis, MTBC, and Trichinella spp.). We demonstrate that monitoring a sentinel species, the polar bear, could be a powerful tool in disease surveillance and highlight the need to better characterize pathogen distributions and diversity in the Arctic.

Brain-heart interaction disruption in major depressive disorder: disturbed rhythm modulation of the cardiac cycle on brain transient theta bursts

Brain neurons support arousal and cognitive activity in the form of spectral transient bursts and cooperate with the peripheral nervous system to adapt to the surrounding environment. However, the temporal dynamics of brain-heart interactions have not been confirmed, and the mechanism of brain-heart interactions in major depressive disorder (MDD) remains unclear. This study aimed to provide direct evidence for brain-heart synchronization in temporal dynamics and clarify the mechanism of brain-heart interaction disruption in MDD. Eight-minute resting-state (closed eyes) electroencephalograph and electrocardiogram signals were acquired simultaneously. The Jaccard index (JI) was used to measure the temporal synchronization between cortical theta transient bursts and cardiac cycle activity (diastole and systole) in 90 MDD patients and 44 healthy controls (HCs) at rest. The deviation JI was used to reflect the equilibrium of brain activity between diastole and systole. The results showed that the diastole JI was higher than the systole JI in both the HC and MDD groups; compared to HCs, the deviation JI attenuated at F4, F6, FC2, and FC4 in the MDD patients. The eccentric deviation JI was negatively correlated with the despair factor scores of the HAMD, and after 4 weeks of antidepressant treatment, the eccentric deviation JI was positively correlated with the despair factor scores of the HAMD. It was concluded that brain-heart synchronization existed in the theta band in healthy individuals and that disturbed rhythm modulation of the cardiac cycle on brain transient theta bursts at right frontoparietal sites led to brain-heart interaction disruption in MDD.

Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

Spotted Fever Group Rickettsiae in Ticks and Small Mammals from Grassland and Forest Habitats in Central Germany

Rickettsiae of the spotted fever group (SFG) are zoonotic tick-borne pathogens. Small mammals are important hosts for the immature life stages of two of the most common tick species in Europe, Ixodes ricinus and Dermacentor reticulatus. These hosts and vectors can be found in diverse habitats with different vegetation types like grasslands and forests. To investigate the influence of environmental and individual factors on Rickettsia prevalence, this study aimed to analyse the prevalence of SFG rickettsiae in ticks and small mammals in different small-scale habitats in central Germany for the first time. Small mammals of ten species and ticks of two species were collected from grasslands and forests in the Hainich-Dün region, central Germany. After species identification, DNA samples from 1098 ticks and ear snips of 1167 small mammals were screened for Rickettsia DNA by qPCR targeting the gltA gene. Positive samples were retested by conventional PCR targeting the ompB gene and sequencing. Rickettsia DNA was detected in eight out of ten small mammal species. Small mammal hosts from forests (14.0%) were significantly more often infected than those from grasslands (4.4%) (p < 0.001). The highest prevalence was found in the mostly forest-inhabiting genus Apodemus (14.8%) and the lowest in Microtus (6.6%), which inhabits grasslands. The prevalence was higher in D. reticulatus (46.3%) than in the I. ricinus complex (8.6%). Adult ticks were more often infected than nymphs (p = 0.0199). All sequenced rickettsiae in I. ricinus complex ticks were R. helvetica, and the ones in D. reticulatus were R. raoultii. Unlike adults, questing nymphs have had only one blood meal, which explains the higher prevalence in I. ricinus adults. Interestingly, habitat type did influence infection probability in small mammals, but did not in ticks. A possible explanation may be the high prevalence in Apodemus flavicollis and A. sylvaticus which were more abundant in the forest.

Early detection of SARS-CoV-2 variants through dynamic co-mutation network surveillance

Background

Precise public health and clinical interventions for the COVID-19 pandemic has spurred a global rush on SARS-CoV-2 variant tracking, but current approaches to variant tracking are challenged by the flood of viral genome sequences leading to a loss of timeliness, accuracy, and reliability. Here, we devised a new co-mutation network framework, aiming to tackle these difficulties in variant surveillance.

Methods

To avoid simultaneous input and modeling of the whole large-scale data, we dynamically investigate the nucleotide covarying pattern of weekly sequences. The community detection algorithm is applied to a co-occurring genomic alteration network constructed from mutation corpora of weekly collected data. Co-mutation communities are identified, extracted, and characterized as variant markers. They contribute to the creation and weekly updates of a community-based variant dictionary tree representing SARS-CoV-2 evolution, where highly similar ones between weeks have been merged to represent the same variants. Emerging communities imply the presence of novel viral variants or new branches of existing variants. This process was benchmarked with worldwide GISAID data and validated using national level data from six COVID-19 hotspot countries.

Results

A total of 235 co-mutation communities were identified after a 120 weeks' investigation of worldwide sequence data, from March 2020 to mid-June 2022. The dictionary tree progressively developed from these communities perfectly recorded the time course of SARS-CoV-2 branching, coinciding with GISAID clades. The time-varying prevalence of these communities in the viral population showed a good match with the emergence and circulation of the variants they represented. All these benchmark results not only exhibited the methodology features but also demonstrated high efficiency in detection of the pandemic variants. When it was applied to regional variant surveillance, our method displayed significantly earlier identification of feature communities of major WHO-named SARS-CoV-2 variants in contrast with Pangolin's monitoring.

Conclusion

An efficient genomic surveillance framework built from weekly co-mutation networks and a dynamic community-based variant dictionary tree enables early detection and continuous investigation of SARS-CoV-2 variants overcoming genomic data flood, aiding in the response to the COVID-19 pandemic.

Zoonotic pathogens linked with hedgehog diphtheric disease

Hedgehog diphtheric disease (HDD), an ulcerative skin disease with a high fatality rate, is an emerging threat to European hedgehogs (Erinaceus europaeus). We explored the potential role of a panel of zoonotic pathogens in the presumed multifactorial nature of HDD in 188 hedgehogs from 3 wildlife rescue centres in Belgium. As expected, and with a prevalence of 67% in 57 hedgehogs with skin lesions, characteristic of HDD, the occurrence of Corynebacterium ulcerans was strongly associated with the disease. Remarkably, with a prevalence of 42% in affected animals, infections with Borrelia burgdorferi sensu lato were 3.92 times more likely to be detected in HDD (95% confidence interval: 1.650-9.880; p = .0024). Overall, 40 hedgehogs tested positive for the B. burgdorferi sensu lato complex, including Borrelia afzelii (n = 30), Borrelia bavariensis (n = 7) and Borrelia spielmanii (n = 7). Other widely occurring pathogens included Salmonella (prevalence of 19%, with three pulsed-field gel electrophoresis profiles) and Leptospira sp. (prevalence of 11%, including Leptospira interrogans and Leptospira borgpetersenii), but these were not associated with the occurrence of HDD. These findings show that hedgehogs in Belgium represent a significant reservoir of multiple zoonotic bacteria, of which toxigenic C. ulcerans and B. burgdorferi sensu lato are associated with widespread hedgehog skin pathology and mortality.

Proposal for multiple new lesions as complement of hyperprogressive disease in NSCLC patients treated with PD-1/PD-L1 immunotherapy

BACKGROUND

Hyperprogressive disease (HPD) is a progression pattern of rapid increase in tumor burden during immunotherapy. However, current HPD definitions are mainly based on the diameter of target lesions. How to take new lesions into account remains unknown.

METHODS

In this retrospectively analysis, 393 patients received PD-1/PD-L1 inhibitors monotherapy. 237 patients were eligible for HPD evaluation based on tumor growth rate (TGR) ratio, ΔTGR or tumor growth kinetic (TGK) ratio. Among them, 214 patients were eligible for evaluation of new lesions. The impact of new lesions on overall survival (OS) was investigated by Kaplan-Meier methods. The optimal threshold for new lesion number was investigated by one-year time-dependent receiver operating characteristic (ROC) curves. Developing more than one new lesions (n ≥ 2) was defined as multiple new lesions (MNL). New HPD was redefined as both developing MNL and meeting the requirement of current HPD definitions (TGR ratio, ΔTGR or TGK ratio). The survival difference between the newly defined HPD and non-HPD patients was investigated.

RESULTS

HPD occurred in 5.1-18.1 % patient based on current definitions (TGR ratio, 15.6 %; ΔTGR, 5.1 %; TGK ratio, 18.1 %). However, there is no significant difference between OS of HPD and non-HPD patient. New lesion was associated with a shorter median OS in PD（with or without HPD) patients (6.1 vs 18.9 months, p = 0.001). Time-dependent ROC analysis suggested that the optimal threshold for new lesion number in survival prediction was two. After the redefinition of HPD, New HPD patients had a significantly shorter median OS compared with non-HPD patients (TGR ratio with MNL: 5.6 vs 11.8 months, p < 0.001; ΔTGR with MNL: 5.0 vs 11.4 months, p = 0.034; TGK ratio with MNL: 5.7 vs 12.3 months, p < 0.001; respectively).

CONCLUSIONS

Current HPD definitions had a better prognostic value when complemented with MNL. MNL should be integrated into the new definition of HPD.

Association between multi-organ dysfunction and adverse outcome in infants with hypoxic ischemic encephalopathy

OBJECTIVE

To evaluate multi-organ dysfunction (MOD) in newborns treated with therapeutic hypothermia (TH) for hypoxic ischemic encephalopathy (HIE), and to compare MOD in those with normal/mild magnetic resonance imaging (MRI) findings to those with moderate to severe MRI findings or death.

STUDY DESIGN

Retrospective single-center observational study of infants treated with TH. A total of 16 parameters across 7 organ systems were analyzed. Primary outcome was death or moderate to severe brain injury on MRI.

RESULT

Of 157 infants treated with TH, 77% had ≥2 organ systems with dysfunction. The number of organ systems with dysfunction was strongly associated with death or moderate-to-severe brain injury (p < 0.0001). Hematologic (68%) and hepatic (65%) dysfunction were most common. Neurologic and renal dysfunction were most strongly associated with the primary outcome (OR 13.5 [6.1-29.8] and 11.2 [4.1-30.3], respectively), while pulmonary hypertension was not.

CONCLUSION

MOD is prevalent in infants undergoing TH for HIE, and the association between MOD and adverse outcomes may impact clinical care and counseling.