We use GALEX ultraviolet (UV) and optical integrated photometry of the hosts of 17 luminous supernovae (LSNe, having peak M-V < -21) and compare them to a sample of 26,000 galaxies from a cross-match between the SDSS DR4 spectral catalog and GALEX interim release 1.1. We place the LSN hosts on the galaxy NUV - r versus M-r color-magnitude diagram (CMD) with the larger sample to illustrate how extreme they are. The LSN hosts appear to favor low-density regions of the galaxy CMD falling on the blue edge of the blue cloud toward the low-luminosity end. From the UV-optical photometry, we estimate the star formation history of the LSN hosts. The hosts have moderately low star formation rates (SFRs) and low stellar masses (M-*) resulting in high specific star formation rates (sSFR). Compared with the larger sample, the LSN hosts occupy low-density regions of a diagram plotting sSFR versus M-* in the area having higher sSFR and lower M-*. This preference for low M-*, high sSFR hosts implies that the LSNe are produced by an effect having to do with their local environment. The correlation of mass with metallicity suggests that perhaps wind-driven mass loss is the factor that prevents LSNe from arising in higher-mass, higher-metallicity hosts. The massive progenitors of the LSNe (> 100 M-circle dot), by appearing in low-SFR hosts, are potential tests for theories of the initial mass function that limit the maximum mass of a star based on the SFR.

Solid waste management represents one of the largest anthropogenic methane emission sources. However, precise quantification of landfill and composting emissions remains difficult due to variety of site-specific factors that contribute to landfill gas generation and effective capture. Remote sensing is an avenue to quantify process-level emissions from waste management facilities. The California Methane Survey flew the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) over 270 landfills and 166 organic waste facilities repeatedly during 2016-2018 to quantify their contribution to the statewide methane budget. We use representative methane retrievals from this campaign to present three specific findings where remote sensing enabled better landfill and composting methane monitoring: (1) Quantification of strong point source emissions from the active face landfills that are difficult to capture by in situ monitoring or landfill models, (2) emissions that result from changes in landfill infrastructure (design, construction, and operations), and (3) unexpected large emissions from two organic waste management methods (composting and digesting) that were originally intended to help mitigate solid waste emissions. Our results show that remotely-sensed emission estimates reveal processes that are difficult to capture in biogas generation models. Furthermore, we find that airborne remote sensing provides an effective avenue to study the temporally changing dynamics of landfills. This capability will be further improved with future spaceborne imaging spectrometers set to launch in the 2020s.

Soil dissolved organic matter (DOM) is the most reactive pool of soil organic matter. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a powerful tool for obtaining molecular-level DOM information. The ongoing atmospheric nitrogen (N) deposition could cause some negative effects on tropical and subtropical forest ecosystems, and biochar is considered to be an effective soil ameliorator. However, few studies have evaluated the effects of biochar and N deposition, either separately or in combination, on the molecular composition of soil DOM. In this study, we conducted a pot experiment using Chinese fir seedlings amended with biochar (0, 12, and 36 t biochar ha-1, prepared from corn stover at 450 C) and inorganic N (NH4NO3: 0, 40, and 80 kg N ha-1 y-1) in a full factorial design (four replications per treatment) and characterized soil DOM using FTICR-MS. A total of 6084 types of formulas were identified in this study. All 36 samples had 2109 types of formulas in common, which had much lower N/C and P/C ratios than the bulk DOM samples. Permutation-based multivariate analysis of variance revealed that both N addition and biochar application had a significant impact on DOM chemodiversity. N addition increased the relative abundance of lignins and lipids, which may be a way for Chinese fir to acclimate to an acidic environment by expanding roots and fixing N. Biochar amendment increased the relative abundance of carbohydrates and tannins in soil DOM at each N application level. Soil pH is a key soil variable controlling DOM composition, and an increase in pH after biochar amendment contributed greatly to the occurrence of DOM compounds with an O/C > 0.5, which are easily degradable. In particular, lignins associated with low N/C were more abundant at higher pH. Biochar application also improved the efficiency of roots in acquiring nutrients, reduced the relative biomass of roots, and decreased the relative content of lignins or lipids, which primarily originated from the roots. In summary, biochar amendment effectively alleviated the negative effects of N addition by investing more N into the production of easily degradable DOM compounds and stimulating the biogeochemical cycle of N.

Increasingly frequent and intense heatwaves threaten ecosystem health in a warming climate. However, plant responses to heatwaves are poorly understood. A key uncertainty concerns the intensification of transpiration when heatwaves suppress photosynthesis, known as transpiration-photosynthesis decoupling. Field observations of such decoupling are scarce, and the underlying physiological mechanisms remain elusive. Here, we use carbonyl sulphide (COS) as a leaf gas exchange tracer to examine potential mechanisms leading to transpiration-photosynthesis decoupling on a coast live oak in a southern California woodland in spring 2013. We found that heatwaves suppressed both photosynthesis and leaf COS uptake but increased transpiration or sustained it at non-heatwave levels throughout the day. Despite statistically significant decoupling between transpiration and photosynthesis, stomatal sensitivity to environmental factors did not change during heatwaves. Instead, midday photosynthesis during heatwaves was restricted by internal diffusion, as indicated by the lower internal conductance to COS. Thus, increased evaporative demand and nonstomatal limitation to photosynthesis act jointly to decouple transpiration from photosynthesis without altering stomatal sensitivity. Decoupling offered limited potential cooling benefits, questioning its effectiveness for leaf thermoregulation in xeric ecosystems. We suggest that adding COS to leaf and ecosystem flux measurements helps elucidate diverse physiological mechanisms underlying transpiration-photosynthesis decoupling.

TurboID-based proximity labeling coupled to mass spectrometry (PL-MS) has emerged as a powerful tool for mapping protein-protein interactions in both plant and animal systems. Despite advances in sensitivity, PL-MS studies can still suffer from false negatives, especially when dealing with low abundance bait proteins and their transient interactors. Protein-level enrichment for biotinylated proteins is well developed and popular, but direct detection of biotinylated proteins by peptide-level enrichment and the difference in results between direct and indirect detection remain underexplored. To address this gap, we compared and improved enrichment and data analysis methods using TurboID fused to SPY, a low-abundance O-fucose transferase, using an AAL-enriched SPY target library for cross-referencing. Our results showed that MyOne and M280 streptavidin beads significantly outperformed antibody beads for peptide-level enrichment, with M280 performing best. In addition, while a biotin concentration less than 50 uM is recommended for protein-level enrichment in plants, higher biotin concentrations can be used for peptide-level enrichment, allowing us to improve detection and data quality. MSFragger protein identification and quantification software outperformed Maxquant and Protein Prospector for SPY interactome enrichment due to its superior detection of biotinylated peptides. Our improved washing protocols for protein-level enrichment mitigated bead collapse issues, improving data quality, and reducing experimental time. We found that the two enrichment methods provided complementary results and identified a total of 160 SPY-TurboID-enriched interactors, including 60 previously identified in the AAL-enriched SPY target list and 100 additional novel interactors. SILIA quantitative proteomics comparing WT and spy-4 mutants showed that SPY affects the protein levels of some of the identified interactors, such as nucleoporin proteins. We expect that our improvement will extend beyond TurboID to benefit other PL systems and hold promise for broader applications in biological research.

Alternative splicing is an important regulatory process in eukaryotes. In plants, the major form of alternative splicing is intron retention. Despite its importance, the global impact of AS on the Arabidopsis proteome has not been investigated. In this study, we address this gap by performing a comprehensive integrated analysis of how changes in AS can affect the Arabidopsis proteome using mutants that disrupt ACINUS and PININ, two evolutionarily conserved alternative splicing factors. We used tandem mass tagging (TMT) with real-time search MS3 (RTS-SPS-MS3) coupled with extensive sample fractionations to achieve very high coverage and accurate protein quantification. We then integrated our proteomic data with transcriptomic data to assess how transcript changes and increased intron retention (IIR) affect the proteome. For differentially expressed transcripts, we have observed a weak to moderate correlation between transcript changes and protein changes. Our studies revealed that some IIRs have no effect on either transcript or protein levels, while some IIRs can significantly affect protein levels. Surprisingly, we found that IIRs have a much smaller effect on increasing protein diversity. Notably, the increased intron retention events detected in the double mutant are also detected in the WT under various biotic or abiotic stresses. We further investigated the characteristics of the retained introns. Our extensive proteomic data help to guide the phenotypic analysis and reveal that collective protein changes contribute to the observed phenotypes of the increased anthocyanin, pale green, reduced growth, and short root observed in the acinus pnn double mutant. Overall, our study provides insight into the intricate regulatory mechanism of intron retention and its impact on protein abundance in plants.

Cell polarity is used to guide asymmetric divisions and create morphologically diverse cells. We find that two oppositely oriented cortical polarity domains present during the asymmetric divisions in the Arabidopsis stomatal lineage are reconfigured into polar domains marking ventral (pore-forming) and outward-facing domains of maturing stomatal guard cells. Proteins that define these opposing polarity domains were used as baits in miniTurboID-based proximity labeling. Among differentially enriched proteins, we find kinases, putative microtubule-interacting proteins, and polar SOSEKIs with their effector ANGUSTIFOLIA. Using AI-facilitated protein structure prediction models, we identify potential protein-protein interaction interfaces among them. Functional and localization analyses of the polarity protein OPL2 and its putative interaction partners suggest a positive interaction with mitotic microtubules and a role in cytokinesis. This combination of proteomics and structural modeling with live-cell imaging provides insights into how polarity is rewired in different cell types and cell-cycle stages.

Alternative splicing is an important regulatory process in eukaryotes. In plants, the major form of alternative splicing is intron retention. Despite its importance, the global impact of AS on the Arabidopsis proteome has not been investigated. In this study, we address this gap by performing a comprehensive integrated analysis of how changes in AS can affect the Arabidopsis proteome using mutants that disrupt ACINUS and PININ, two evolutionarily conserved alternative splicing factors. We used tandem mass tagging (TMT) with real-time search MS3 (RTS-SPS-MS3) coupled with extensive sample fractionations to achieve very high coverage and accurate protein quantification. We then integrated our proteomic data with transcriptomic data to assess how transcript changes and increased intron retention (IIR) affect the proteome. For differentially expressed transcripts, we have observed a weak to moderate correlation between transcript changes and protein changes. Our studies revealed that some IIRs have no effect on either transcript or protein levels, while some IIRs can significantly affect protein levels. Surprisingly, we found that IIRs have a much smaller effect on increasing protein diversity. Notably, the increased intron retention events detected in the double mutant are also detected in the WT under various biotic or abiotic stresses. We further investigated the characteristics of the retained introns. Our extensive proteomic data help to guide the phenotypic analysis and reveal that collective protein changes contribute to the observed phenotypes of the increased anthocyanin, pale green, reduced growth, and short root observed in the acinus pnn double mutant. Overall, our study provides insight into the intricate regulatory mechanism of intron retention and its impact on protein abundance in plants.

At a rapid pace, biologists are learning the many ways in which resident microbes influence, and sometimes even control, their hosts to shape both health and disease. Understanding the biochemistry behind these interactions promises to reveal completely novel and targeted ways of counteracting disease processes. However, in our protocols and publications, we continue to describe these new results using a language that originated in a completely different context. This language developed when microbial interactions with hosts were perceived to be primarily pathogenic, as threats that had to be vanquished. Biomedicine had one dominating thought: winning this war against microorganisms. Today, we know that beyond their defensive roles, host tissues, especially epithelia, are vital to ensuring association with the normal microbiota, the communities of microbes that persistently live with the host. Thus, we need to adopt a language that better encompasses the newly appreciated importance of host-microbiota associations. We also need a language that frames the onset and progression of pathogenic conditions within the context of the normal microbiota. Such a reimagined lexicon should make it clear, from the very nature of its words, that microorganisms are primarily vital to our health, and only more rarely the cause of disease.This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

All animals and plants likely require interactions with microbes, often in strong, persistent symbiotic associations. While the recognition of this phenomenon has been slow in coming, it will impact most, if not all, subdisciplines of biology.