SAMPLE COLLECTION APPARATUS AND METHOD FOR PREPARING A PLURALITY OF LIQUID SAMPLES FOR SAMPLE PROCESSING

Abstract

A sample collection apparatus, being configured for preparing a plurality of liquid samples for a sample processing, includes a collection device including a plurality of collection vessels being configured for accommodating the liquid samples and for providing the liquid samples for the sample processing, wherein the sample collection apparatus is shaped for positioning the collection device directly in a carousel of an autosampler apparatus, in particular a liquid chromatography autosampler apparatus. Preferably, a holder device is provided which is configured for holding the collection device during collecting the liquid samples and during providing the liquid samples for the sample processing, and the holder device is shaped for positioning the holder device with the collection device directly in the carousel of the autosampler apparatus. Furthermore, a sample preparation apparatus including the sample collection apparatus and a sample collection method are described.

Claims

1. A sample collection apparatus, being configured for preparing a plurality of liquid samples for a sample processing, comprising: a collection device comprising a plurality of collection vessels being configured for accommodating the liquid samples and for providing the liquid samples for the sample processing, wherein the sample collection apparatus is shaped for positioning the collection device directly in a carousel of an autosampler apparatus.

2. The sample collection apparatus according to claim 1, wherein the sample collection apparatus is shaped for positioning the collection device directly in a carousel of a liquid chromatography autosampler apparatus.

3. The sample collection apparatus according to claim 1, further comprising: a holder device being configured for holding the collection device during collecting the liquid samples and during providing the liquid samples for the sample processing, and the holder device is shaped for positioning the holder device with the collection device directly in the carousel of the autosampler apparatus.

4. The sample collection apparatus according to claim 3, wherein a bottom side of the holder device has an outer shape of a sample rack of the autosampler apparatus.

5. The sample collection apparatus according to claim 3, wherein the holder device is made of a material with a thermal conductivity being matched to the thermal conductivity of a metal.

6. The sample collection apparatus according to claim 5, wherein the metal is aluminum or stainless steel.

7. The sample collection apparatus according to claim 3, wherein the holder device has a substrate section being configured for accommodating the collection device and a lid section being configured for covering the collection device accommodated on the substrate section.

8. The sample collection apparatus according to claim 1, wherein the sample preparing apparatus has at least two receptacles being configured for receiving coupling elements of the autosampler apparatus.

9. The sample collection apparatus according to claim 1, wherein the collection device has an outer size of a standard microscopy glass slide or a microtiter plate.

10. A sample preparation apparatus, comprising: the sample collection apparatus according to claim 1, and an autosampler apparatus.

11. The sample preparation apparatus according to claim 10, wherein the autosampler apparatus is a liquid chromatography autosampler apparatus.

12. A sample collection method for preparing liquid samples for sample processing, comprising the steps of: collecting the liquid samples with a collection device comprising a plurality of collection vessels each being configured for accommodating one of the liquid samples and for providing the liquid samples for the sample processing; and positioning the collection device directly in a carousel of an autosampler apparatus.

13. The sample collection method according to claim 12, wherein the liquid samples are prepared for liquid chromatography sample separation.

14. The sample collection method according to claim 12, wherein the collection device is positioned directly in a carousel of a liquid chromatography autosampler apparatus.

15. The sample collection method according to claim 12, wherein: the collection device is arranged on a holder device being configured for holding the collection device during collecting the liquid samples and during providing the liquid samples for the sample processing, and positioning the collection device comprises positioning the holder device directly in the carousel of the autosampler apparatus.

16. The sample collection method according to claim 15, wherein a temperature of the liquid samples is set by setting a temperature of the autosampler apparatus and tempering the collection device via the holder device.

17. The sample collection method according to claim 12, wherein: the collection device is covered with a lid section, and the liquid samples are taken by puncturing the lid section with an autosampler needle of the autosampler apparatus at a time of sample loading.

18. The sample collection method according to claim 12, further comprising a step of preloading the collection vessels of the collection device with at least one of an organic solution and at least one of an organic and aqueous solution for at least one of lysis and digestion steps.

19. The sample collection method according to claim 18, wherein the organic solution comprises an oil.

20. A method of using the sample collection apparatus according to claim 1 for preparing liquid samples before sample processing with a liquid chromatography autosampler apparatus.

21. The method according to claim 20, including using the sample collection apparatus for preparing liquid samples before sample processing with the liquid chromatography autosampler apparatus for mass spectrometry analyses.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Further advantages and details of the invention are described in the following with reference to the attached drawings, which schematically show in:

[0058] FIGS. 1 and 2: top and cross-sections views of collections devices of a sample collection apparatus according to embodiments of the invention;

[0059] FIGS. 3 to 6: top and side views of holder devices of a sample collection apparatus according to embodiments of the invention;

[0060] FIG. 7: an illustration of the proteoChipproteoCHIP based TMT-labeling workflow. Up to sixteen nanowells/single cells per TMT set are prepared inside the cellenONE®, are automatically combined via centrifugation and directly interfaced with a standard autosampler for loss-less acquisition;

[0061] FIG. 8: an illustration of an application of the proteoCHIP for single cell proteomics sample preparation with TMT10-plex and TMTpro reagents at different carrier compositions. (a) Number of identified proteins, peptides, PSMs, all MS/MS scans and the ID rate for TMT10-plex (red) and TMTpro (green). Error bars represent median absolute deviation. (b) Log.sub.10 S/N of all single cell reporter ions at indicated condition over five replicates. Log.sub.2 S/N correlation between two single cell samples for (c) TMT10-plex 20× carrier, (d) TMT10-plex no carrier, (e) TMTpro 20× carrier and (f) TMTpro no carrier. r=Pearson correlation estimate.;

[0062] FIG. 9: an illustration of data completeness and reproducibility evaluation of multiplexed single cell proteomes. Unique peptide sequence overlaps for (a) TMT10-plex 20× carrier, (b) TMT10-plex no carrier, (c) TMTpro 20× carrier and (d) TMTpro no carrier samples. Percentage of relative missing reporter ions across five analytical runs per PSM for (e) TMT10-plex 20× carrier, (f) TMT10-plex no carrier, (g) TMTpro 20× carrier and (h) TMTpro no carrier samples. Cumulative missing quantitative data across five analytical runs for (i) TMT10-plex 20× carrier, (j) TMT10-plex no carrier, (k) TMTpro 20× carrier and (I) TMTpro no carrier samples.;

[0063] FIG. 10: a comparison of HeLa and HEK single cell proteomes. (a) Protein groups, peptides, PSMs, MS/MS scans and ID-rate of TMT10-plex HeLa/HEK samples. (b) Intensity distribution of all reporter ions for both HeLa and HEK single cells across several analytical runs in login (n=11). (c) PCA clustering of single HeLa (blue) and HEK (red) TMT10-plex labeled 110 single cells across 976 protein groups. (d) Vulcano plot of differential expressed proteins between HeLa and HEK single cells. Log.sub.2 fold change and -login p-value is shown. Colors indicate protein regulation and top up- or down regulated proteins are labeled with their gene names;

[0064] FIG. 11: an illustration of a Label-free proteome analysis of single HeLa cells. (a) Protein groups of indicated cell numbers via direct injection from the funnel (red) or transferred to a standard PCR vial (blue). (b) Protein groups, peptides, PSMs, all MS/MS scans and the ID-rate of label-free single cells (n=32). Error bars represent median absolute deviation. (c) Unique peptide sequence overlap of three label-free single HeLa measurements. (d) Label-free protein quantification correlation of two analytical runs in log.sub.2. r=Pearson correlation estimation.;

[0065] FIG. 12: Gravy index of hydropathy of bulk HeLa digest (bulk), in-silico digested human FASTA (in-silico), HeLa cells prepared in standard plasticware (PP), the proteoCHIP (PTFE) and prepared in the proteoCHIP but transferred to a standard PCR vial for injection (Transfer) across all PSMs; and

[0066] FIG. 13: an image of a HEK and a HeLa cell during image-based cell sorting using the cellenONE®.

DESCRIPTION OF PREFERRED EMBODIMENTS

[0067] Features of preferred embodiments of the invention are described in the following with exemplary reference to sample preparation for the LC-MS/MS analysis. It is emphasized, that the application of the invention is not restricted to this embodiment, but correspondingly possible with other analyses, e. g. by using other samples and reagents. Furthermore, while the sample preparing apparatus is schematically shown, details, like e. g. the number, shape and size of the arrays and reactions sites and/or the number, shape and size of the collection device(s) can be modified in dependency on the particular applications conditions. Details of the sample processing for proteomics investigations are not described as far as they are known per se from conventional techniques. Exemplary reference is made to the use of a collection device as described in [28]. The invention is not restricted to this embodiment, but can be implemented in a corresponding manner with other configurations of collection devices, e. g. having the shape of a micro-titer plate or a nano-titer plate.

[0068] FIGS. 1a and 1b illustrate a collection device as disclosed in [28]. Twelve collections vessels each with a vessel opening and a vessel bottom are arranged for accommodating liquid samples. As shown in FIG. 1b, the collections vessels have an inner shape with a pyramid-shaped or cone-shaped bottom section and a cube shaped upper section. The size of 75*25 mm corresponds to the standard size of a microscopy slide glass.

[0069] As described in [28], the collection device can be combined with a carrier plate device with an array of reaction sites, wherein the carrier plate device is configured for accommodating the samples and supplying reagents to the liquid samples. The reaction sites can be preloaded with at least one of an organic solution, in particular an oil, and an organic and/or aqueous solution for lysis and/or digestion steps. Preloading with an oil may prevent evaporation of the subsequent aqueous droplets.

[0070] FIGS. 2a and 2b illustrate an alternative collection device being shaped like a standard 96 well microtiter plate. 96 collections vessels each with a vessel opening and a vessel bottom are arranged for accommodating liquid samples. Again, as shown in FIG. 2b, the collections vessels have an inner shape with a pyramid-shaped or cone-shaped bottom section and a cube shaped upper section.

[0071] FIGS. 3a and 3b illustrate a holder device being configured for holding three collection devices according to FIG. 1. On an upper side (right side in FIG. 3b), the holder device has three receptacles for accommodating the collection devices. On a lower side (left side in FIG. 3b), the holder device has two holes for accommodating pillars of a carousel of an autosampler apparatus (not shown).

[0072] FIGS. 4a and 4b illustrate a holder device being configured for holding one collection device according to FIG. 2. On an upper side (right side in FIG. 4b), the holder device has one receptacles for accommodating the collection device. On a lower side (left side in FIG. 4b), the holder device has two holes for accommodating pillars of a carousel of an autosampler apparatus (not shown).

[0073] While FIGS. 1 to 4 refer to examples wherein the sample collection apparatus has two components, comprising the collection device and the holder device, the sample collection apparatus may be configured with a single component functioning as the collection device accommodating the sample and the holder device matching with the carousel of an autosampler apparatus, as shown in FIGS. 5 and 6. FIG. 5 shows the sample collection apparatus with a lid covering all collection vessels, and FIG. 6 shows the collection vessels being arranged like in a 96 well microtiter plate.

[0074] FIG. 7 illustrates sample handling with the embodiment of FIG. 1, as described with further details in [28], and the direct connection of the sample collection apparatus with the autosampler apparatus.

[0075] In the following practical tests of the inventive technique are described with reference to FIGS. 7 to 12.

[0076] Sample Preparation

[0077] HeLa and HEK293T cells were cultured at 37° C. and 5% CO2 in Dulbecco's Modified Eagle's Medium supplemented with 10% FBS and 1× penicillin-streptomycin (P0781-100ML, Sigma-Aldrich, Israel) and L-Glut (25030-024, Thermo Scientific, Germany). After trypsinization (0.05% Trypsin-EDTA 1×, 25300-054, Sigma-Aldrich, USA/Germany), cells were pelleted, washed 3× with phosphate-buffered saline (PBS) and directly used for single cell experiments.

[0078] 40-200 nL lysis buffer (0.2% DDM (D4641-500MG, Sigma-Aldrich, USA/Germany), 100 mM TEAB (17902-500ML, Fluka Analytical, Switzerland), 20 ng/μL trypsin (Promega Gold, V5280, Promega, USA) was dispensed into each well using the cellenONE® (Cellenion, France) at high humidity. After single cell deposition (gated for cell diameter min 22 μm and diameter max 33 μm, circularity 1.1, elongation 1.84) a layer of Hexadecane (H6703-100ML, Sigma-Aldrich, USA/Germany) was added to the chips. The chip was then incubated at 50° C. for 30 minutes followed by 4 hrs at 37° C., directly on the heating deck inside the cellenONE®. For TMT multiplexed experiments 100-200 nL of 22 mM TMT10-plex or TMTpro in anhydrous ACN was added to the respective wells and incubated for 1 hour at room-temperature. TMT was subsequently quenched with 50 nL 0.5% hydroxylamine (90115, Thermo Scientific, Germany) and 3% HCl followed by sample pooling via centrifugation using the proteoCHIP funnel part. After tryptic digest, label-free samples were quenched with 0.1% TFA and both label-free or multiplexed samples were either transferred to 0.2 mL PCR-tubes coated with 1e-3% Poly(ethylene glycol) (95172-250G-F, Sigma-Aldrich, Germany), directly injected from the proteoCHIP funnel part or kept at −20° C. until usage.

[0079] LC-MS/MS Analysis

[0080] Samples were measured on a Orbitrap Exploris™ 480 Mass Spectrometer (Thermo Fisher Scientific) with a reversed phase Dionex Thermo Fisher Scientific UltiMate 3000 RSLC-nano high-performance liquid chromatography (HPLC) RSLCnano system coupled via a Nanospray Flex ion source equipped with FAIMS (operated at −50 CV). Labeled peptides were first trapped on an Acclaim™ PepMap™ 100 C18 precolumn (5 μM, 0.3 mm×5 mm, Thermo Fisher Scientific) and eluted to the analytical column nanoEase M/Z Peptide BEH C18 Column (130 Å, 1.7 μm, 75 μm×150 mm, Waters, Germany) developing a two-step solvent gradient ranging from 2 to 20% over 45 min and 20 to 32% ACN in 0.08 formic acid within 15 min, at a flow rate of 250 nL/min. Label-free samples were measured on the same setup as described above but separated using a two-step gradient from 2 to 20% over 15 min, 20 to 32% ACN in 0.08 formic acid within 5 minutes, at 250 nL/min.

[0081] Full MS data of multiplexed experiments were acquired in a range of 375-1,200 m/z with a maximum AGC target of 3e6 and automatic inject time at 120,000 resolution. Top 10 multiply charged precursors (2-5) over a minimum intensity of 5e3 were isolated using a 2 Th isolation window. MS/MS scans were acquired at a resolution of 60,000 at a fixed first mass of 110 m/z with a maximum AGC target of 1e5 or injection time of 118 ms. Previously isolated precursors were subsequently excluded from fragmentation with a dynamic exclusion of 120 seconds. TMT10-plex precursors were fragmented at a normalized collision energy (NCE) of 34 and TMTpro at a NCE of 32.

[0082] Data Analysis

[0083] Peptide identification was performed using the standard parameters in Spectromine™ 2.0 against the human reference proteome sequence database (UniProt; version: 2020 Oct. 12). N-terminal protein acetylation and oxidation at methionine were set as variable modifications and the respective TMT reagents were selected as fixed modification. PSM, peptide and protein groups were filtered with a false discovery rate (FDR) of 1%. S/N levels of reporter ions were extracted using the in-house developed Hyperplex (freely available: pd-nodes.org) at 10 ppm and intersected with the Spectromine™ results. Post-processing was performed in the R environment. Single cell reporter ion intensities are normalized to their sample loading within each analytical run. For HeLa HEK clustering, the raw reporter ion intensities were log2 transformed, protein groups with less than 70% missing data across the entire dataset were imputed with random values from a normal distribution shifted into the noise. The reporter ion intensities were then quantile normalized, batch corrected using ComBat for the analytical run and the TMT channel using the Perseus interface.11 Venn Diagrams are based on unique peptide sequences and are calculated using BioVenn.12 GRAVY scores were calculated for every unique peptide sequence identified from the respective condition, based on the Amino Acid Hydropathy Scores.13

[0084] The inventors tested the inventive sample collection apparatus for automated single cell proteomics sample preparation within a platform combining single cell isolation and picoliter dispensing, the cellenONE®, for both label-free and multiplexed samples. The sample collection apparatus is a complete system in the size of standard microscopy slides that is constituted of two parts. First, the carrier plate device (well part) is where the single cell isolation and sample preparation takes place and, secondly, the collection device (funnel part) is where the samples can be combined before direct interfacing for injection in the LC autosampler. The first part entails twelve fields to process twelve label-free single cells or twelve multiplexed sample sets with up to sixteen cells per set (total 192 cells) (FIG. 7, see [28]). The carrier plate device has four main advantages over other published sample preparation workflows [8-10,14]. First, to overcome known peptide losses to plastic or glass ware [15,16] the proteoCHIP is fabricated out of PTFE or a plastics material having properties like PTFE. Despite the similar GRAVY indices of samples analyzed in bulk, from the PTFE sample collection apparatus, after transfer to a PP vessel or preparation in PP plates (FIG. 12), the inventors regularly observe beneficial peptide recovery from samples processed in PTFE . Second, the nanowells within each field hold up to 600 nL allowing to readily adapt the sample preparation protocol without cross-contamination of the samples. Third, in contrast to successfully miniaturized sample preparation strategies1 the inventors overcome sample evaporation with a hexadecane layer (FIG. 7). Hexadecane freezing point is close to 18° C., the oil covering the final sample in the 10° C. autosampler therefore freezes and does not interfere with the subsequent analysis. This results in constant reagent and enzyme concentrations in relation to the cells for reproducible processing efficiencies. Additionally, all fields are surrounded by elevated walls, physically separating each sample set during the workflow and storage in the autosampler. Fourth, the proteoCHIP funnel part allows convenient polling of multiplexed single cell samples using a standard benchtop plate centrifuge (FIG. 7). In contrast to the N2 workflow where nested single cells are elegantly combined via the addition of a drop of sample buffer,8 the proteoCHIP funnel part can be directly interfaced with a standard autosampler. This allows for direct injection of the samples without drying or transferring them to another vessel (FIG. 7). Taken together, the reduction in processing volumes, manual sample handling and exposed surface areas combined with the direct interface to a standard autosampler attain single cell proteome measurements at remarkable sensitivity.

[0085] Single Cell Proteomics Sample Preparation Workflow with the Sample Collection Apparatus

[0086] The inventors performed the entire sample preparation workflow inside the cellenONE® starting with dispensing of a master mix for lysis and enzymatic digestion followed by image-based single-cell isolation, where cells are directly dispensed in the master mix. We use a combination of a MS compatible detergent to ensure efficient lysis with simultaneous tryptic digestion at a 10:1 enzyme:substrate ratio. Lysis and digestion incubation steps at 50 and 37° C. are performed at high humidity (i.e. 85%) while the sample is submerged under a hexadecane layer to overcome evaporation (detailed in the method section). Subsequent steps are performed at dew point to further reduce sample evaporation and residual enzymatic activity during the labeling. Afterwards, excess TMT is quenched with hydroxylamine and hydrochloric acid to avoid drastic changes in pH. Of note, this protocol allows for a final sample volume after lysis, digestion, TMT-labeling and quenching of sub-microliter without drying the sample to completeness.

[0087] Subsequently, the proteoCHIP is covered with proteoCHIP funnel part, pooled in a centrifuge within only a minute, covered with adhesive aluminum foil, which can be easily pierced by the HPLC puncturer and finally injected for LC-MS/MS analysis (illustrated in FIG. 7).

[0088] Multiplexed Single Cell Proteome Measurements.

[0089] First, the inventors evaluated the required abundance of the carrier spike for comparable protein identifications to state of the art techniques [8,10]. The optimized workflow using the sample collection apparatus with reduced sample volume, manipulation and surface area exposure allows to reduce the carrier to merely 20× or lower, yielding around 1,000 protein groups per analytical run (FIG. 8a). This ratio reduction of the carrier to single cells close to the reported ratio limit of TMT10-plex reagents improves quantification accuracy [17,18]. In detail, the inventors readily identify on average 1,175 and 897 protein groups based on 4,832 and 3,444 peptides per multiplexed TMT10-plex set using a 20× carrier or no carrier, respectively (FIG. 8a). All TMT10-plex single cell runs combined (i.e. 306 single cells) yield over 2,023 protein groups based on 13,601 peptides. Similarly, the 20× and no carrier TMTpro samples (i.e. 276 single cells) result in an average of 1,017 and 924 protein groups from 3,873 and 3,833 peptides per analytical run, respectively (FIG. 8a). Across all TMTpro single cell sets, the inventors identify over 2,016 protein groups from 12,180 peptides. This indicates that the inventors find multiple protein groups uniquely in some analytical runs and not across all replicates for both TMT reagents. Nevertheless, our specialized workflow resulted in highly comparable identifications for both TMT reagents and with the reduced or omitted carrier.

[0090] Recently, Cheung and co-workers proposed a signal to noise (S/N) filtering for more accurate quantification of multiplexed single cell proteomics experiments [18]. The inventors therefore extracted the S/N value of all single cell channels using our in-house software Hyperplex (details in method section) and evaluated the S/N distribution for our experimental setup. The average single cell S/N in all conditions from cells prepared with the sample collection apparatus on the instrument setup well compares or outperforms previous reports. In detail, the inventors observed median single cell reporter ion S/N values of 40 and 100 for TMT10-plex samples or 133 and 255 for TMTpro samples, with and without the 20× carrier, respectively (FIG. 8b). Despite being acquired on different instruments, the setup and the carrier reduction vastly improves S/N reporter values compared to 7-15 S/N of the nanoPOTS or N2 [6,8,19].

[0091] Interestingly, TMTpro experiments with and without the carrier resulted in higher S/N of the single cell channels compared to the TMT10-plex (FIG. 8b). the inventors have regularly observed this phenomenon in trace samples and speculate, that this is due to the reduced NCE needed to fragment the TMTpro over the TMT10-plex reagent. The TMTpro NCE of 32 efficiently fragments the tag and is close to the energy required for fragmentation of the peptide backbone. This contrasts with the slightly higher NCE of 34 required to suitably fragment the TMT10-plex tag, possibly increasing the noise level in each MS/MS scan. Furthermore, the inventors observed a reduction by 50% in single cell S/N in the 20× carrier compared to the no-carrier samples, for both TMT10-plex and TMTpro experiments (FIG. 8b). Despite the low ratio of the carrier to the single cells, the inventors speculate that this is due to the increased proportion of ions sampled from the carrier [18] or compression of the single cell reporter ion signals into the noise. Additionally, a pairwise correlation of two single cell reporter ion channels demonstrates increased variance between the 20× carrier compared to the no carrier samples for both TMT10-plex and TMTpro (FIGS. 8c-f). Despite the obvious beneficial aspects of a carrier spike20, based on our findings, the inventors agree with literature to reduce the carrier to a minimum or if possible, remove it entirely from the TMT set [6,18].

[0092] Next, based on the presumed low identification overlap between analytical runs (i.e. biological replicates), the inventors evaluated the unique peptide sequence intersections and percentage of missing data within our single cell runs. Interestingly, the inventors observed less overlap in unique peptide sequences for the TMTpro compared to TMT10-plex samples for 20× and no carrier setups, ranging from 50 to 85% (FIG. 9a-d). The inventors found that both, the stochastic precursor selection of the employed data dependent acquisition (DDA) strategy and the direct injection of the sample after TMT labeling without a cleanup compromise reproducibility. Furthermore, the inventors speculate that nearly double the TMT reagent in the final TMTpro compared to the TMT10-plex sample, contributes background signal, interferes with precursor selection and MS/MS identification, additionally decreasing peptide sequence overlap (FIG. 9a-d). Accordingly, the inventors evaluated both the missingness of reporter ion signal per PSM and the cumulative missing data across multiple analytical runs. The high reporter ion S/N already suggested that the signal of our single cells is well above the noise therefore resulting in almost no missing values per PSM for all experimental setups (FIG. 9e-h). Even with the low missingness per analytical run, the high variance between analytical runs leads to cumulative missing quantitative data (FIGS. 9i-l). The data aggregation of five analytical runs (i.e. about 50-80 single cells) reduces the number of confidently quantified proteins by 50% without imputation (FIGS. 9i-l), as reported by others [8,10]. This demonstrates that despite the high quality quantitative data per analytical run, the untargeted data dependent acquisition (DDA) results in accumulation of missing data in large sample cohorts [21,22]. As a result the acquired dataset is either drastically reduced or a large proportion of quantitative data is computationally generated.

[0093] Differentiating two similarly sized human cell types based on their single cell proteome.

[0094] Following the surprising data quality stemming from our optimized sample preparation workflow, the inventors tested if two similarly sized human cell types can be differentiated based on their proteome (FIG. 13). The inventors used 110 HeLa and HEK single cell samples using the inventive workflow and distributed them equally across eleven TMT10-plex sets. Both, the 20× carrier and no carrier samples yield on average around 1,300 protein groups based on 5,000 peptides per analytical run (FIG. 10a). Further, the inventors confirmed that the similarly sized cells contain similar protein amounts, resulting in equally distributed reporter ion intensities in all TMT10-plex channels across multiple analytical runs (FIG. 10b). This not only indicates highly reproducible sample preparation but also strengthens our confidence that the differences the inventors observe between the cell types originate from changes in the proteome and not different sample input. The inventors therefore performed a principal component analysis of the two cell types and observed a cell type specific separation via the first two components (FIG. 10c). Of note, even though the inventors filtered for at least 70% quantitative data completeness, the cell type cluster density decreases the more analytical runs were accumulated. The inventors found that this is in part due to the reduced sample overlap introduced by stochastic precursor picking and elevated background signals as described earlier (FIG. 9a-d). Consequently, the inventors strongly believe that the optimization of in-line, loss-less sample clean-up in conjunction with an efficient data independent acquisition (DIA) strategy will further improve our results.

[0095] Aiming at examining the cluster loadings in more detail, the inventors investigated top differentially expressed proteins between the two cell types (FIG. 10c-d). Interestingly, one of the top hits in HeLa cells compared to HEK cells is the brain acid soluble protein 1 (BASP1), which is downregulated in most tumor cell lines except some cervical cancer lines (FIG. 10d). In contrast to other cancer cell lines, the elevated levels of the tumor suppressor BASP1 in HeLa cells even promotes tumor growth [24]. Alongside BASP1, cross referencing of our top regulated proteins to normalized expression data obtained from the Human Protein Atlas [23] (http://www.proteinatlas.org) revealed strong agreement (i.e. TMSB10, FOLR1, TMSB4X, LGALS1, KRT7, SLC7A5, KRT8, PARP1, CD44, PGRMC1, BASP1). Following this, the inventors accurately represent quantitative differences between the two cell types and that our analysis distinguishes the two solely based on their proteome. Of note, using our experimental setup, the inventors can directly correlate changes in the proteome to the acquired image during cell sorting by the cellenONE®. This allows to estimate if an expected or unexpected clustering behavior is a result of the respective proteome or can be traced back to the preparation and cellular morphology.

[0096] Label-Free Single Cell Proteome Acquisition with the Sample Collection Apparatus

[0097] The inventors investigated how the multiplexed sample preparation workflow compares in the generation of label-free single cells. Label-free proteome analysis has several advantages over multiplexed sample workflows, like the direct MS1 based quantification, the possibility of highly confident feature matching between analytical runs and the reduced chemical noise introduced by the labeling [25,26]. The inventors therefore evaluated the sample collection apparatus protocol in the analysis of label-free single cell samples, using shorter gradients based on the vastly reduced sample input (i.e. 30 minutes compared to 60 minutes for TMT-labeled samples). This still drastically reduces the throughput of the acquired samples, however, the gradient length and overhead times between the samples is still subject to further improvement. First, the inventors processed increasing numbers of HeLa cells starting from only one up to 6 cells, either transferring the sample to a standard PP vial for injection or measuring directly via the proteoCHIP funnel part (FIG. 7). As expected, the sample transfer results in slight peptide losses more prominent in the lower cell input samples compared to five cells and more (FIG. 11a). Even though the samples are processed identically and transferred to a PEG pre-treated PP vial, the vessel exchange results on average in 30% decreased protein identifications for single cells. The inventors found that these differences are especially striking at such low input, as this readily declines to only 10% for two cells and merely 5% in the analysis of three cells (FIG. 11a). This indicates that the direct connection and reduced sample manipulation enabled by the proteoCHIP is critical in the analysis of single cell proteomes.

[0098] The optimized label-free sample collection apparatus workflow reproducibly yields around 500 protein groups per single HeLa cell and 1.422 protein groups across all 30 single cell measurements. Interestingly, similarly to the TMT-labeled samples (FIG. 9a-d), the unique peptide sequence overlap between three replicates is only around 50% (FIG. 11c). Despite that, peptides that were identified across replicates positively correlated with a pearson correlation estimate of 0.662 (FIG. 11d). The inventors found that this drastic reduction in replicate overlap again is mostly caused by the stochastic selection of precursors in DDA strategies. Even though label-free measurements now allow for FDR-controlled match between runs based on MS1 features [25], the inventors are confident that the transition to DIA measurements will improve replicate overlap and quantification correlation. Further, the inventors found that the fast duty cycles and the increased usage of the ion beam of the PASEF strategy on the timsTOF Pro will benefit our label-free single cell analysis [27]. Taken together, the inventors have successfully extended the sample processing capabilities of the proteoCHIP to label-free single cell samples at surprising sensitivity. However, the inventors hypothesize that the data reproducibility can be further advanced via specialized acquisition strategies.

[0099] In summary, the inventors demonstrate the improvement of single cell sample preparation using the sample collection apparatus in conjunction with a commercial single cell isolation and picoliter dispenser, e. g. the cellenONE®. The proposed sample preparation workflow of single cells for MS-based analysis is highly adaptable and allows for the preparation of label-free or multiplexed single cells. The optimized protocol drastically reduces the digest volumes compared to previously published well-based techniques and is comparable to those successfully applied in nanoPOTS [1,10,14]. This not only limits chemical noise but as a result of the hexadecane layer covering the sample, the inventors achieve constant enzyme and chemical concentrations increasing efficiency of the sample preparation. Further, the specialized design of the proteoCHIP allows automatic pooling of multiplexed samples using a standard benchtop centrifuge, final sample collection in the proteoCHIP funnel part and direct interfacing with a standard autosampler for LC-MS/MS analysis. This semi-automated processing, pooling, and injecting eliminates error prone manual sample handling often resulting in peptide losses and additional variance.

[0100] The inventive efficient single cell sample preparation retains comparable protein identifications and improved S/N of single cell reporter ions even at reduced or eliminated carrier (FIG. 8a-b) [8,10]. This not only allows increased throughput by labelling single cells with all available TMT reagents but also improves the confidence of identifying peptides stemming from the single cells and not the carrier [18]. The inventors further show that two highly similar human cell types can be differentiated based on their proteome using our platform (FIG. 9c). The inventors are therefore confident that biologically similar cell types (e.g. originating from the same organ) can be classified and profiled using our workflow. The inventors, however, acknowledge that despite the good correlation of individual samples (FIGS. 8c-f) the correlation and replicate overlap between analytical runs is still subject to improvements (FIGS. 9a-d). Despite the suboptimal replicate correlation, the over 75% data completeness within one analytical run (FIGS. 9e-h) leaves the inventors confident that DIA workflows will further advance present results. The inventors propose that specialized DIA methods for the Orbitrap Exploris or diaPASEF on the timsTOF Pro will drive reproducibility at similar quantification accuracy. Further, the inventive optimized sample processing strategy in conjunction with the more sensitive, second generation timsTOF Pro will further increase identifications especially of label-free single cell samples [2].

[0101] Concluding, the miniaturized single cell proteomics sample preparation workflow with the novel sample collection apparatus utilizes standard chemicals for MS-based sample preparation. Employing a versatile picoliter dispensing robot, the cellenONE®, the inventors have achieved efficient single cell proteomics sample preparation which can be readily adapted, addressing multiple shortcomings of previously-published label-free and multiplexed methods.

[0102] The features of the invention disclosed in the above description, the drawings and the claims can be of significance both individually as well as in combination or sub-combination for the realization of the invention in its various embodiments.