In
our previous work, we have demonstrated an integrated proteome
analysis device (iPAD-100) to analyze proteomes from 100 cells. In this work, for the first time, a novel integrated
device for single-cell analysis (iPAD-1) was developed to profile
proteins in a single cell within 1 h. In the iPAD-1, a selected single
cell was directly sucked into a 22 μm i.d. capillary. Then the
cell lysis and protein digestion were simultaneously accomplished
in the capillary in a 2 nL volume, which could prevent protein loss
and excessive dilution. Digestion was accelerated by using elevated
temperature with ultrasonication. The whole time of cell treatment
was 30 min. After that, single-cell digest peptides were transferred
into an LC column directly through a true zero dead volume union,
to minimize protein transfer loss. A homemade 22 μm i.d. nano-LC
packing column with 3 μm i.d. ESI tip was used in the device
to achieve ultrasensitive detection. A 30 min elution program was
applied to analysis of the single-cell proteome. Therefore, the total
time needed for a single-cell analysis was only 1 h. In an analysis
of 10 single HeLa cells, a maximum of 328 proteins were identified
in one cell by using an Orbitrap Fusion Tribrid MS instrument, and
the detection limit was estimated at around 1.7–170 zmol. Such
a sensitivity of the iPAD-1 was ∼120-fold higher than that
of our previously developed iPAD-100 system. Prominent cellular heterogeneity in protein expressive profiling
was observed. Furthermore, we roughly estimated the phases of the
cell cycle of tested HeLa cells by the amount of core histone proteins.
The heterogeneous
populations of exosomes with distinct nanosize
have impeded our understanding of their corresponding function as
intercellular communication agents. Profiling signaling proteins packaged
in each size-dependent subtype can disclose this heterogeneity of
exosomes. Herein, new strategy was developed for deconstructing heterogeneity
of distinct-size urine exosome subpopulations by profiling N-glycoproteomics
and phosphoproteomics simultaneously. Two-dimension size exclusion
liquid chromatography (SEC) was utilized to isolate large exosomes
(L-Exo), medium exosomes (M-Exo), and small exosomes (S-Exo) from
human urine samples. Then, hydrophilic carbonyl-functionalized magnetic
zirconium-organic framework (CFMZOF) was developed as probe for capturing
the two kinds of post-translational modification (PTM) peptides simultaneously.
Finally, liquid chromatography-tandem mass spectrometry (LC-MS/MS)
combined with database search was used to characterize PTM protein
contents. We identified 144 glycoproteins and 44 phosphoproteins from
L-Exo, 156 glycoproteins, and 46 phosphoproteins from M-Exo and 134
glycoproteins and 10 phosphoproteins from S-Exo. The ratio of the
proteins with simultaneous glycosylation and phosphorylation is 11%,
9%, and 3% in L-Exo, M-Exo, and S-Exo, respectively. Based on label-free
quantification intensity results, both principal component analysis
and Pearson’s correlation coefficients indicate that distinct-size
exosome subpopulations exist significant differences in PTM protein
contents. Analysis of high abundance PTM proteins in each exosome
subset reveals that the preferentially packaged PTM proteins in L-Exo,
M-Exo, and S-Exo are associated with immune response, biological metabolism,
and molecule transport processes, respectively. Our PTM proteomics
study based on size-dependent exosome subtypes opens a new avenue
for deconstructing the heterogeneity of exosomes.
Plasma exosomes have shown great potential for liquid biopsy in clinical cancer diagnosis. Herein, we present an integrated strategy for isolating and analyzing exosomes from human plasma rapidly and then discriminating different cancers excellently based on deep learning fingerprints of plasma exosomes. Sequential sizeexclusion chromatography (SSEC) was developed efficiently for separating exosomes from human plasma. SSEC isolated plasma exosomes, taking as less as 2 h for a single sample with high purity such that the discard rates of high-density lipoproteins and low/ very low-density lipoproteins were 93 and 85%, respectively. Benefitting from the rapid and high-purity isolation, the contents encapsulated in exosomes, covered by plasma proteins, were well profiled by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS). We further analyzed 220 clinical samples, including 79 breast cancer patients, 57 pancreatic cancer patients, and 84 healthy controls. After MS data preprocessing and feature selection, the extracted MS feature peaks were utilized as inputs for constructing a multi-classifier artificial neural network (denoted as Exo-ANN) model. The optimized model avoided overfitting and performed well in both training cohorts and test cohorts. For the samples in the independent test cohort, it realized a diagnosed accuracy of 80.0% with an area under the curve of 0.91 for the whole group. These results suggest that our integrated pipeline may become a generic tool for liquid biopsy based on the analysis of plasma exosomes in clinics.
Efficient isolation and downstream bioinformation analysis of circulating tumor cells (CTCs) in whole blood contribute to the early diagnosis of cancer and investigation of cancer metastasis. However, the separation and release of CTCs remain a great challenge due to the extreme rarity of CTCs and severe interference from other cells in complex clinical samples. Herein, we developed a low-cost and easy-to-fabricate aptamer-functionalized wafer with a three-dimensional (3D) interconnected porous structure by grafting polydopamine (PDA), poly(ethylene glycol
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