Data-independent acquisition (DIA) mass spectrometry has grown in popularity in recent years, because of the reproducibility and quantitative rigor of a systematic tandem mass spectrometry (MS/MS) sampling method. However, traditional DIA methods may spend valuable instrument time acquiring MS/MS spectra with no usable information in them, affecting sensitivity and quantitative performance. We developed a DIA strategy that dynamically adjusts the MS/MS windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time─increasing the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.
The standard approach for proteomic data acquisition of isobaric-tagged samples by mass spectrometry is data-dependent acquisition. This semistochastic, identification-first paradigm generates a wealth of peptide-level data without regard to relative abundance. We introduce a data acquisition concept called sequential windowed acquisition of reporter masses (SWARM). This approach performs quantitation first, thereby allowing subsequent acquisition decisions to be predicated on user-defined patterns of reporter ion intensities. The efficacy of this approach is validated through experiments with both synthetic mixtures of Escherichia coli ribosomes spiked into human cell lysates at known ratios and the quantitative evaluation of the human proteome's response to the inhibition of cullin-based protein ubiquitination via the small molecule MLN4924. We find that SWARM-informed parallel reaction monitoring acquisitions display effective acquisition biasing toward analytes displaying quantitative characteristics of interest, resulting in an improvement in the detection of differentially abundant analytes. The SWARM concept provides a flexible platform for the further development of new acquisition methods.
Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation is crucial for site localization in O-glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of N-glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized O-glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both N-and O-glycopeptides within the same LC-MS/MS acquisition.
Plant cryptochromes undergo blue light-dependent phosphorylation to regulate their activity and abundance, but the protein kinases that phosphorylate plant cryptochromes have remained unclear. Here we show that photoexcited Arabidopsis cryptochrome 2 (CRY2) is phosphorylated in vivo on as many as 24 different residues, including 7 major phosphoserines. We demonstrate that four closely related Photoregulatory Protein Kinases (previously referred to as MUT9-like kinases) interact with and phosphorylate photoexcited CRY2. Analyses of the ppk123 and ppk124 triple mutants and amiR4k artificial microRNA-expressing lines demonstrate that PPKs catalyse blue light-dependent CRY2 phosphorylation to both activate and destabilize the photoreceptor. Phenotypic analyses of these mutant lines indicate that PPKs may have additional substrates, including those involved in the phytochrome signal transduction pathway. These results reveal a mechanism underlying the co-action of cryptochromes and phytochromes to coordinate plant growth and development in response to different wavelengths of solar radiation in nature.
Abstract The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25–50%) than euchromatic reference regions (3–11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11–27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4–3.6 vs. 8.4–8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu.
Abstract Identification and structural characterization of novel metabolites in drug discovery or metabolomics experiments is one of the most challenging tasks. Multi-level fragmentation (MS n ) based approaches combined with various dissociation modes are frequently utilized for facilitating structure assignment of the unknown compounds. As each of the MS precursors undergoes MS n , the instrument cycle time can limit the total number of precursors analyzed in a single run for complex samples. This necessitates splitting data acquisition into several LC/MS analyses where the results obtained in one acquisition inform the experimental design for the successive experiment. Here we present a new LC/MS data acquisition strategy, termed Met-IQ, where the decision to perform an MS n acquisition is automatically made in real time based on the similarity between an acquired experimental MS 2 spectrum and a spectrum in a reference spectral library. Each MS 2 spectrum is searched in real time against the spectra for the known compounds of interest. If a similarity to a spectrum in the library is found, the instrument performs a decision-dependent event, such as an MS 3 scan. Compared to an intensity-based, data-dependent MS n experiment, only a selective number of MS 3 are triggered using Met-IQ, increasing the overall MS 2 instrument sampling rate. We applied this strategy to an Amprenavir sample incubated with human liver microsomes. The number of MS 2 scan events increased nearly 3.5-fold compared to the standard data dependent experiment where MS 3 was triggered for each precursor ion, resulting in identification and structural characterization of 55% more unique metabolites. Furthermore, the MS 3 precursor fragments were selected intelligently, focusing on higher mass fragments of sufficient intensity to maximize acquisition of MS 3 data relevant for structure assignment. The described Met-IQ strategy is not limited to metabolism experiments, and can be applied to analytical samples where the detection of unknown compounds structurally related to a known compound(s) is sought.
Abstract Background: COVID-19 disrupted the healthcare system and services across the cancer continuum. Early on, breast and cervical (B & C) screenings were effectively halted, and many diagnostic and treatment procedures delayed. Emerging evidence suggests that uninsured populations and patients of color were disproportionately affected, but less is known about rural-urban differences. The Illinois Breast and Cervical Cancer Screening Program (IBCCP), administered by agencies across 102 counties, provides screening and diagnostic services for low-income, uninsured, and underinsured persons. This study assesses the impact of COVID-19 on agencies’ administrative functions and clients’ ability to receive services, and to examine rural-urban differences. Methods: IBCCP coordinators were invited to complete an online survey that asked about COVID-19’s effect on administrative functions and services at two different time periods, the height of the pandemic and in the past month (11/2021-12/2021). Chi-square and Fisher’s exact tests were used to examine differences between rural and urban agencies (classified by using the 2013 NCHS Urban-Rural Classification Scheme).Results: In total, 32 agencies (50% urban, 50% rural), responded. Concerning administrative functions, in the past month compared to at the height of the pandemic, fewer agencies overall reported that COVID-19 had a moderate to great impact (compared to occasional or no impact) on staffing (47% vs. 74%) and client enrollment (34% vs. 90%). Although not significant, more rural than urban agencies reported effects on staffing (56% vs. 38%) and enrollment (50% vs. 19%) in the past month. Concerning clients’ ability to receive services, in the past month compared to the height of the pandemic, fewer agencies overall reported COVID-19 effects on screening (31% vs. 75%), diagnostic (19% vs. 61%), and treatment (3% vs. 38%) services. Some rural-urban differences were noted; at the height of the pandemic, urban agencies were more likely to report effects on diagnostic (88% vs. 33%, p=.002) and treatment (56% vs. 19%, p=.028) services when compared to rural. Although not significant, in the past month, more urban (vs. rural) agencies reported COVID-19 related effects on screening (44% vs. 19%), diagnostic (31% vs. 6%), and treatment (7% vs. 0%) services. Conclusion: Overall, agencies implementing this safety net program are generally rebounding from the pandemic’s effect on administrative functions and clients’ ability to receive services. However, rural and urban agencies may be differentially affected by the pandemic. For example, in the past month, a greater proportion of rural agencies reported effects on administrative functions Interestingly, more urban agencies reported lingering effects on clients’ ability to receive screening and diagnostic services. These trends suggest that rural and urban agencies may be differentially affected by the pandemic and geographically tailored responses may best support recovery. Citation Format: Leslie R. Carnahan, Ananya Stoller, William Barshop, Genevieve Rizzo, Arden Handler. Assessing the impact of the COVID-19 pandemic on a statewide breast and cervical cancer safety net screening and diagnostic program: Are there differences by rural – urban geography? [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A053.
Abstract Toxoplasma gondii is an obligate intracellular parasite that utilizes peripheral membrane and cytoskeletal structures for critical functions such as host cell invasion, replication, and maintaining cellular morphology. These structures include the inner membrane complex (IMC) as well as the underlying longitudinal subpellicular microtubules (SPMTs) that provide support for the IMC and give the parasite its distinctive crescent shape. While the IMC and SPMTs have been studied on their own, the mechanisms linking these adjacent structures remain largely unknown. This study identifies a T. gondii protein named IMT1 that localizes to the maternal IMC and SPMTs and thus appears to tether the IMC to the microtubules. We disrupt the IMT1 gene to assess function and then use deletion analyses and mutagenesis to reveal regions of the protein that are necessary for binding to the IMC cytoskeleton or SPMTs. Using proximity labelling with IMT1 as bait, we identify a series of candidate interactors in the IMC or SPMTs. Exploration of two of these candidates reveals that IMT1 regulates the levels of the microtubule associated protein TLAP2 and binds directly to the cytoskeletal IMC protein IMC1. Taken together, these interactions unveil the specific interactions linking two key cytoskeletal structures of the parasite and provides new insight into the organization of the structural backbone of T. gondii .
Multiplexed proteomics has become a powerful tool for investigating biological systems. Using balancer-peptide conjugates (e.g., TMTproC complementary ions) in the MS2 spectra for quantification circumvents the ratio distortion problem inherent in multiplexed proteomics. However, TMTproC quantification scans require long Orbitrap transients and extended ion injection times to achieve sufficient ion statistics and spectral resolution. Real-Time Search (RTS) algorithms have demonstrated increased speed and sensitivity by selectively informing precursor peak quantification. Here, we combine complementary ion quantification with Real-Time Search (TMTproC-RTS) to enhance sensitivity while maintaining accuracy and precision in quantitative proteomics at the MS2 level. We demonstrate the utility of this method by quantifying protein dynamics during the embryonic development of Drosophila melanogaster (fly), Ciona robusta (sea squirt), and Xenopus laevis (frog). We quantify 7.8k, 8.6k, and 12.7k proteins in each organism, which is an improvement of 12%, 13%, and 14%, respectively, compared to naive TMTproC analysis. For all three organisms, the newly acquired data outperform previously published datasets and provides a diverse, deep, and accurate database of protein dynamics during embryogenesis which will advance the study of evolutionary comparison in early embryogenesis.
