Using LC-MS/MS for determination of low-abundance protein biomarkers from dried blood spots is challenging due to the combination of low biomarker levels (low pM-level) and small sample volumes (typically <50 μL). In the present paper it is demonstrated that use of state-of-the-art nano liquid chromatography triple quadrupole mass spectrometry in combination with immunoaffinity sample clean-up enable determination of the low abundance biomarker human chorionic gonadotropin (hCG) from four different biological matrices (whole blood, serum, plasma and urine) at its upper reference level (low pM). Detection limits for hCG was determined for all matrices from both commercially available non-soluble DBS sampling material (DMPK-C) and the water-soluble material carboxymethyl cellulose (CMC). The detection limits (S/N = 3) were ranging from 5.0 IU/L (14.5 pM; whole blood) to 10.5 IU/L (30.5 pM; urine) for DMPK-C and from 2.1 IU/L (6.1 pM; urine) to 6.4 IU/L (18.6 pM; plasma) for CMC. A brief evaluation was performed for both sampling materials using serum as matrix resulting in sufficient linearity (r ≥ 0.93, range 20-1000 IU/mL (58-2900 pM) for DMPK-C and 10-1000 IU/mL (29-2900 pM) for CMC), repeatability (RSD% = 13-31%) and accuracy (95-106%). To demonstrate the applicability of the method to real samples, a serum sample from a patient previously diagnosed with cancer was also analyzed using both sampling materials. The concentration levels found using the two materials were similar (5280± 595 IU/L (15,312 ± 1726 pM, n = 3) in the DMPK-C spot and 5060 ± 430 IU/L (14,674 ± 1247 pM, n = 3) in the CMC spot). All in all this demonstrated that the tools for determination of low abundance biomarkers at upper reference level from dried matrix spots now is available through a combination of immunoaffinity enrichment and state-of-the-art LC-MS/MS.

Biological fluids such as urine, saliva and whole blood were analyzed for contents of drugs by a new combination of desorption electrospray ionization mass spectrometry (DESI-MS) and thin liquid membrane extraction (TLME). Analytes from the sample were extracted into a thin liquid membrane of hexadecane deposited on a porous Teflon membrane, from which they were subsequently analyzed directly by DESI. The total analysis time was 15 minutes for analysis of several samples with a potential analysis time of less than a minute per sample. Thanks to the pre-concentration and sample clean-up built into the method, methadone was detected in urine in full-scan mode with an LOD of 4 ng mL(-1), while amitriptyline, nortriptyline and pethidine showed LODs of 17 ng mL(-1). Quantification was possible for several basic drugs using one common internal standard, providing relative accuracies in the range of 10-30%. A reliability test was performed on 20 samples with methadone, amitriptyline, nortriptyline and pethidine in urine, showing that none of the samples having concentrations above the LOD were missed and no false positives were found. Diphenhydramine and one of its metabolites were detected in authentic samples of urine and saliva, and methadone was detected from a whole-blood sample spiked to a concentration of 100 ng mL(-1). The method has several advantages, such as extremely low price in consumables, the possibility of fast analysis of very crude biofluids such as whole blood and the potential for a very high sample throughput.

A concept integrating sampling and protein digestion is introduced here combining fast and simple fabrication by wax printing on filter paper with trypsin immobilized polymer beads. The paper reactors showed promising results with a high degree of protein digestion within fifty minutes in model protein mixtures as well as in human blood. The model protein mixture was used for the evaluation of performance both with and without a reduction and alkylation step. The paper reactors without reduction and alkylation showed between 46% and 75% protein sequence coverage and between five and 20 high confidence peptides (one and five zero missed cleavage peptides, respectively). Compared to a conventional in-solution approach, the paper reactor showed 10% less protein sequence coverage, 29% fewer high confidence peptides and 19% fewer high confidence peptides with zero missed cleavages. Placement of the protein reduction and alkylation step (before or after protein digestion) was shown to be of low importance. The storage stability of the paper reactors with (six weeks) and without (twelve weeks) tryptic peptides was satisfactory. The ability of the paper reactors to digest complex biological samples was investigated by comparison with human whole blood samples prepared using a conventional dried blood spot (DBS) procedure with overnight digestion in non-targeted analysis. The reactors showed a comparable performance with 75 ± 25 for the protein groups compared to 76 ± 5 for the DBS samples. Additionally, 267 ± 72 and 335 ± 11 unique peptides (high confidence) were identified for on-paper digestion and DBS, respectively.

Despite the great potential of dried blood spots (DBS) as a source of endogenous proteins for biomarker discovery, the literature relating to nontargeted bottom-up proteomics of DBS is sparse, primarily due to the inherent complexity and very high dynamic range associated with these samples. Here, we present proof-of-concept results in which we have coupled high field asymmetric waveform ion mobility spectrometry (FAIMS) with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for nontargeted bottom-up proteomics of DBS with the aim of addressing these challenges. We, and others, have previously demonstrated the benefits of FAIMS more generally in proteomics including improved signal-to-noise and extended proteome coverage, and the aim of the current work was to extend those benefits specifically to DBS. The DBS samples were either extracted by the more traditional manual "punch and elute" approach or by an automated liquid surface extraction (LESA) approach prior to trypsin digestion. The resulting samples were analyzed by LC-MS/MS and LC-FAIMS-MS/MS analysis. The results show that the total number of proteins identified increased by ∼50% for the punch and elute samples and ∼45% for the LESA samples in the LC-FAIMS-MS/MS analysis. For both the punch and elute samples and the LESA samples, ∼30% of the total proteins identified were observed in both the LC-MS/MS and the LC-FAIMS-MS/MS data sets, illustrating the complementarity of the approaches. Overall, this work demonstrates the benefits of inclusion of FAIMS for nontargeted proteomics of DBS.