	<rdf:RDF xmlns:admin="http://webns.net/mvcb/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:prism="http://purl.org/rss/1.0/modules/prism/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/">
	<channel rdf:about="https://biorxiv.org">
	<admin:errorReportsTo rdf:resource="mailto:biorxiv@cshlpress.edu"/>
	<title>bioRxiv Channel: Parallel Squared Technology Institute</title>
	<link>https://biorxiv.org</link>
	<description>
	This feed contains articles for bioRxiv Channel "Parallel Squared Technology Institute"
	</description>

		<items>
	<rdf:Seq>
		</rdf:Seq>
	</items>
	<prism:eIssn/>
	<prism:publicationName>bioRxiv</prism:publicationName>
	<prism:issn/>

	<image rdf:resource=""/>
	</channel>
	<image rdf:about="">
	<title>bioRxiv</title>
	<url/>
	<link>https://biorxiv.org</link>
	</image>
	<item rdf:about="https://biorxiv.org/cgi/content/short/2025.05.22.655512v1?rss=1">
<title>
<![CDATA[
JMod: Joint modeling of mass spectra for empowering multiplexed DIA proteomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2025.05.22.655512v1?rss=1"
</link>
<description><![CDATA[
The throughput of mass spectrometry (MS) proteomics can be increased substantially by multiplexing that enables parallelization of data acquisition. Such parallelization in the mass domain (plexDIA) and the time domain (timePlex) increases the density of mass spectra and the overlap between ions originating from different precursors, potentially complicating their analysis. To enhance sequence identification and quantification from such spectra, we developed an open source software for Joint Modeling of mass spectra: JMod. It uses the intrinsic structure in the spectra and explicitly models overlapping peaks as linear superpositions of their components. This modeling enabled performing 9-plexDIA using 2 Da offset PSMtags by deconvolving the resulting overlapping isotopic envelopes in both MS1 and MS2 space. The results demonstrate 9-fold higher throughput with preserved quantitative accuracy and coverage depth. This support for smaller mass offsets increases multiplexing capacity and thus proteomic throughput for a given plexDIA tag, and we demonstrate this generalizability with diethyl labeling. By supporting enhanced decoding of DIA spectra multiplexed in the mass and time domains, JMod provides an open and flexible software that enables increasing the throughput of sensitive proteomics.
]]></description>
<dc:creator>McDonnell, K.</dc:creator>
<dc:creator>Wamsley, N.</dc:creator>
<dc:creator>Derks, J.</dc:creator>
<dc:creator>Sipe, S.</dc:creator>
<dc:creator>Yeh, M.</dc:creator>
<dc:creator>Specht, H.</dc:creator>
<dc:creator>Slavov, N.</dc:creator>
<dc:date>2025-05-27</dc:date>
<dc:identifier>doi:10.1101/2025.05.22.655512</dc:identifier>
<dc:title><![CDATA[JMod: Joint modeling of mass spectra for empowering multiplexed DIA proteomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2025-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2025.05.22.655509v1?rss=1">
<title>
<![CDATA[
PSMtags improve peptide sequencing and throughput in sensitive proteomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2025.05.22.655509v1?rss=1"
</link>
<description><![CDATA[
Mass spectrometry-based proteomics enables comprehensive characterization of protein abundance, function, and interactions. Label-free approaches are simple to implement but challenging to scale to thousands of samples per day. Multiplexed techniques, such as plexDIA, can address these limitations but remain restricted by the lack of mass tags optimized for data-independent acquisition (DIA) workflows. Here, we present a systematic approach screening a library of 576 compounds that identifies several small molecules that, when conjugated to peptides, improve their detection and sequence identification by mass spectrometry. The lead molecule, PSMtag, substantially increases the detection of fragment b-ions, which increases the confidence of sequence identification and enhances de novo sequencing. PSMtags allow 9-plexDIA, using only stable isotopes of carbon, oxygen and nitrogen. As a result, it allows simultaneously increasing proteome coverage and sample throughput for plexDIA workflows without compromising quantitative accuracy. We demonstrate 240 samples-per-day with 9-plexDIA, while acquiring 28,359 protein data points in the same time label-free methods acquire 4,340. Our approach constitutes an expandable framework for designing mass tags to overcome existing limitations in multiplexed proteomics and provides plexDIA reagents capable of analyzing over 1,000 samples per day when using 10 minute runs. By facilitating higher throughput and improved identification, this innovation holds significant potential for accelerating proteomic studies across diverse biological and clinical applications.
]]></description>
<dc:creator>Specht, H.</dc:creator>
<dc:creator>Yeh, M.</dc:creator>
<dc:creator>Sipe, S.</dc:creator>
<dc:creator>Barnes-Seeman, D.</dc:creator>
<dc:creator>Adamo, M.</dc:creator>
<dc:creator>McDonnell, K.</dc:creator>
<dc:creator>Agius, M. P.</dc:creator>
<dc:creator>Friedrich, C.</dc:creator>
<dc:creator>Pang, W. K.</dc:creator>
<dc:creator>Huang, Y.</dc:creator>
<dc:creator>Shiva Raju, K.</dc:creator>
<dc:creator>Vuong, W.</dc:creator>
<dc:creator>Lee, M. A.</dc:creator>
<dc:creator>Yesilcimen, A.</dc:creator>
<dc:creator>Pentelute, B. L.</dc:creator>
<dc:creator>Slavov, N.</dc:creator>
<dc:date>2025-05-27</dc:date>
<dc:identifier>doi:10.1101/2025.05.22.655509</dc:identifier>
<dc:title><![CDATA[PSMtags improve peptide sequencing and throughput in sensitive proteomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2025-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2025.05.22.655515v1?rss=1">
<title>
<![CDATA[
Increasing mass spectrometry throughput using time-encoded sample multiplexing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2025.05.22.655515v1?rss=1"
</link>
<description><![CDATA[
Liquid chromatography-mass spectrometry (LC-MS) can enable precise and accurate quantification of analytes at high-sensitivity, but the rate at which samples can be analyzed remains limiting. Throughput can be increased by multiplexing samples in the mass domain with plexDIA, yet multiplexing along one dimension will only linearly scale throughput with plex. To enable combinatorial-scaling of proteomics throughput, we developed a complementary multiplexing strategy in the time domain, termed  timePlex. timePlex staggers and overlaps the separation periods of individual samples. This strategy is orthogonal to isotopic multiplexing, which enables combinatorial multiplexing in mass and time domains when paired together, and thus multiplicatively increased throughput. We demonstrate this with 3-timePlex and 3-plexDIA, enabling the multiplexing of 9 samples per LC-MS run, and 3-timePlex and 9-plexDIA exceeding 500 samples / day with a combinatorial 27-plex. Crucially, timePlex supports sensitive analyses, including of single cells. These results establish timePlex as a methodology for label-free multiplexing and combinatorial scaling of the throughput of LC-MS proteomics. We project this combined approach will eventually enable an increase in throughput exceeding 1,000 samples / day.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/655515v1_ufig1.gif" ALT="Figure 1">
View larger version (20K):
org.highwire.dtl.DTLVardef@1c1d799org.highwire.dtl.DTLVardef@1319339org.highwire.dtl.DTLVardef@1b8bf4borg.highwire.dtl.DTLVardef@16d9e9_HPS_FORMAT_FIGEXP  M_FIG C_FIG
]]></description>
<dc:creator>Derks, J.</dc:creator>
<dc:creator>McDonnell, K.</dc:creator>
<dc:creator>Wamsley, N.</dc:creator>
<dc:creator>Stewart, P.</dc:creator>
<dc:creator>Yeh, M.</dc:creator>
<dc:creator>Specht, H.</dc:creator>
<dc:creator>Slavov, N.</dc:creator>
<dc:date>2025-05-27</dc:date>
<dc:identifier>doi:10.1101/2025.05.22.655515</dc:identifier>
<dc:title><![CDATA[Increasing mass spectrometry throughput using time-encoded sample multiplexing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2025-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2025.05.29.656728v1?rss=1">
<title>
<![CDATA[
Ubiquitin-Proteasome System Dysregulation in Alzheimer's Disease Impacts Protein Abundance 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2025.05.29.656728v1?rss=1"
</link>
<description><![CDATA[
Alzheimers disease (AD) is a relentlessly progressive, fatal neurodegenerative disorder associated with widespread aberrant proteomic changes. The full extent of protein dysfunctions in AD and their impact on cellular physiology remains unknown. Here, we used plexDIA, an approach that parallelizes the acquisition of samples and peptides, to characterize proteomic changes in AD. Using human dorsolateral prefrontal cortex tissue, we identified 281 differentially abundant proteins in AD. By systematically analyzing cellular compartment-specific shifts in protein abundance, we identified an AD-specific decrease in levels of the 20S proteasome, the catalytic core of the cells primary protein degradation pathway. This alteration was accompanied by widespread decreases in proteasome subunit stoichiometries. Many proteasome substrate proteins were negatively correlated with 20S levels and increased in AD, suggesting that reduced 20S levels leads to abnormal protein accumulation. By analyzing proteins increased in AD, we identify key properties of such proteins. Namely, they have highly specific subcellular localizations and fast degradation rates, they contain signal sequences that allow them to be targeted for proteasomal degradation, and they are targeted by quality control pathways that recognize mislocalized proteins. Furthermore, we identify coherent sets of ubiquitin system enzymes, proteins that target substrates for proteasomal degradation, whose levels robustly discriminate AD from non-AD samples. One subset exhibited consistent increases in AD, while another exhibited consistent decreases, revealing complex alterations to the ubiquitin system in AD. Taken together, our results suggest that decreased ubiquitin-proteasome system capacity and impaired clearance of short-lived and mislocalized proteins contribute substantially to proteopathic burden in AD.
]]></description>
<dc:creator>Collins, M. A.</dc:creator>
<dc:creator>Friedrich, C.</dc:creator>
<dc:creator>Elcheikhali, M.</dc:creator>
<dc:creator>Stewart, P.</dc:creator>
<dc:creator>Derks, J.</dc:creator>
<dc:creator>Connors Stewart, T.</dc:creator>
<dc:creator>Altig, K.</dc:creator>
<dc:creator>Melloni, A.</dc:creator>
<dc:creator>Petelski, A.</dc:creator>
<dc:creator>Oakley, D.</dc:creator>
<dc:creator>Hyman, B.</dc:creator>
<dc:creator>Slavov, N.</dc:creator>
<dc:date>2025-05-29</dc:date>
<dc:identifier>doi:10.1101/2025.05.29.656728</dc:identifier>
<dc:title><![CDATA[Ubiquitin-Proteasome System Dysregulation in Alzheimer's Disease Impacts Protein Abundance]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2025-05-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2025.10.22.679607v1?rss=1">
<title>
<![CDATA[
How to design 1000-plex mass tags using the differential mass defect 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2025.10.22.679607v1?rss=1"
</link>
<description><![CDATA[
Multiplexing samples in mass spectrometry-based proteomics has long been accomplished by iso-topologues of small molecules. These chemically-identical "mass tags" conjugate to peptides to encode samples with different mass offsets for parallel analysis. The current state-of-the-art for multiplexing with non-isobaric mass tags was recently improved from 3-plex to 9-plex, but what is the largest plex size that can be reasonably achieved with current technology? A full answer to this question requires evaluating current mass spectrometry hardware, facets of which have been well-investigated by others. However, it may be underappreciated that multiplexing 1000s of samples with mass tags does not actually require 1000s of isotopes, or 1000s of synthesis steps to create. Non-intuitively, high plex mass tags can require relatively few different isotopes. The focus of this exposition is to characterize the potential of the differential mass defect to create tens to over a thousand isotopologues of small molecules and how careful combinations of these small molecules can combinatorially scale the plex size to minimize synthetic steps. Importantly, we show that plex sizes in the hundreds, an order of magnitude greater than state-of-the-art, are achievable using molecules comparable in size to existing commercial tags, and that going beyond hundreds may require larger molecules. Approaches to achieve high-plex proteomics will almost certainly require using the differential mass defect, so we hope this exposition serves to accelerate progress in reagent development to achieve high plex proteomics.
]]></description>
<dc:creator>Specht, H.</dc:creator>
<dc:creator>McDonnell, K.</dc:creator>
<dc:creator>Agius, M. P.</dc:creator>
<dc:date>2025-10-23</dc:date>
<dc:identifier>doi:10.1101/2025.10.22.679607</dc:identifier>
<dc:title><![CDATA[How to design 1000-plex mass tags using the differential mass defect]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2025-10-23</prism:publicationDate>
<prism:section></prism:section>
</item>
</rdf:RDF>
