In recent years, the concept of cell heterogeneity in biology has gained increasing attention, concomitant with a push toward technologies capable of resolving such biological complexity at the molecular level. For single-cell proteomics using Mass Spectrometry (scMS) and low-input proteomics experiments, the sensitivity of an orbitrap mass analyzer can sometimes be limiting. Therefore, low-input proteomics and scMS could benefit from linear ion traps, which provide faster scanning speeds and higher sensitivity than an orbitrap mass analyzer, however at the cost of resolution. We optimized an acquisition method that combines the orbitrap and linear ion trap, as implemented on a tribrid instrument, while taking advantage of the high-field asymmetric waveform ion mobility spectrometry (FAIMS) pro interface, with a prime focus on low-input applications. First, we compared the performance of orbitrap-versus linear ion trap mass analyzers. Subsequently, we optimized critical method parameters for low-input measurement by data-independent acquisition on the linear ion trap mass analyzer. We conclude that linear ion traps mass analyzers combined with FAIMS and Whisper flow chromatography are well-tailored for low-input proteomics experiments, and can simultaneously increase the throughput and sensitivity of large-scale proteomics experiments where limited material is available, such as clinical samples and cellular subpopulations.

Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, mass spectrometry-based single-cell proteomics (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carried out comprehensive analysis of orbitrap-based data independent acquisition (DIA) for limited material proteomics. Notably, we found a fundamental difference between optimal DIA methods for high- and low-load samples. We further improved our low-input DIA method by relying on high-resolution MS1 quantification, thus more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we were able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we establish a complete experimental scp-MS workflow, combining DIA with accessible single-cell sample preparation and the latest chromatographic and computational advances and showcase our developments by profiling real single cells.

Expression of exon-specific isoforms from alternatively spliced mRNA is a fundamental mechanism that substantially expands the proteome of a cell. However, conventional methods to assess alternative splicing are either consumptive and work-intensive or do not quantify isoform expression longitudinally at the protein level. Here, we therefore developed an exon-specific isoform expression reporter system (EXSISERS), which non-invasively reports the translation of exon-containing isoforms of endogenous genes by scarlessly excising reporter proteins from the nascent polypeptide chain through highly efficient, intein-mediated protein splicing. We applied EXSISERS to quantify the inclusion of the disease-associated exon 10 in microtubule-associated protein tau (MAPT) in patient-derived induced pluripotent stem cells and screened Cas13-based RNA-targeting effectors for isoform specificity. We also coupled cell survival to the inclusion of exon 18b of FOXP1, which is involved in maintaining pluripotency of embryonic stem cells, and confirmed that MBNL1 is a dominant factor for exon 18b exclusion. EXSISERS enables non-disruptive and multimodal monitoring of exon-specific isoform expression with high sensitivity and cellular resolution, and empowers high-throughput screening of exon-specific therapeutic interventions.

A linear ion trap (LIT) is an affordable, robust mass spectrometer that provides fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry (MS) measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on the column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

Despite their fundamental role in assessing (patho)physiological cell states, conventional gene reporters can follow gene expression but leave scars on the proteins or substantially alter the mature messenger RNA. Multi-time-point measurements of non-coding RNAs are currently impossible without modifying their nucleotide sequence, which can alter their native function, half-life and localization. Thus, we developed the intron-encoded scarless programmable extranuclear cistronic transcript (INSPECT) as a minimally invasive transcriptional reporter embedded within an intron of a gene of interest. Post-transcriptional excision of INSPECT results in the mature endogenous RNA without sequence alterations and an additional engineered transcript that leaves the nucleus by hijacking the nuclear export machinery for subsequent translation into a reporter or effector protein. We showcase its use in monitoring interleukin-2 (IL2) after T cell activation and tracking the transcriptional dynamics of the long non-coding RNA (lncRNA) NEAT1 during CRISPR interference-mediated perturbation. INSPECT is a method for monitoring gene transcription without altering the mature lncRNA or messenger RNA of the target of interest.

A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

In recent years, the concept of cell heterogeneity in biology has gained increasing attention, concomitant with a push towards technologies capable of resolving such biological complexity at the molecular level. While RNA-based approaches have long been the method of choice, advances in mass spectrometry (MS)-based technologies have led to the ability to resolve cellular proteomes within minute sample quantities and, very recently, even down to a single cell. Current limitations are the incomplete proteome depth achieved and low sample throughput, and continued efforts are needed to push the envelope on instrument sensitivity, improved data acquisition methods, and chromatography. For single-cell proteomics using Mass Spectrometry (scMS) and low-input proteomics experiments, the sensitivity of an orbitrap mass analyzer can sometimes be limiting. Therefore, low-input proteomics and scMS could benefit from linear ion traps, which provide faster scanning speeds and higher sensitivity than an orbitrap mass analyzer, however, at the cost of resolution. We optimized and improved an acquisition method that combines the orbitrap and linear ion trap, as implemented on a tribrid instrument, while taking advantage of the high-field asymmetric waveform ion mobility spectrometry (FAIMS) pro interface, with a prime focus on low-input applications. First, we compared the performance of orbitrap- versus linear ion trap mass analyzers. Subsequently, we optimized critical method parameters for low-input measurement by data-independent acquisition (DIA) on the linear ion trap mass analyzer. We conclude that linear ion traps mass analyzers combined with FAIMS and WhisperTM flow chromatography are well-tailored for low-input proteomics experiments. They can simultaneously increase the throughput and sensitivity of large-scale proteomics experiments where limited material is available, such as clinical samples, cellular sub-populations, and eventually, scMS.