Profiling and annotation of human kidney glomerulus proteome

Table 1 Summary of proteins identified by Mascot and Spectrum Mill

A Proteins identified by Spectrum Mill
	Number of identified proteins
Protein pre-fractionation	High confidence ^a	Low confidence ^b	Total identified proteins ^c
1-D pre-fractionation^d	2354	1066	3420
2-D pre-fractionation^e
Fr. 1 (pH 3–4.6)	1189	708	1897
Fr. 2 (pH 4.6-5.4)	1753	827	2580
Fr. 3 (pH 5.4-6.2)	1423	886	2309
Fr. 4 (pH6.2-7.0)	2228	909	3137
Fr. 5 (pH 7.0-10.0)	1699	841	2540
Total number^f	8292	4171	12463
Total distinct proteins^g	4322	1875	6197
Total distinct genes^h			2085
B Proteins identified by Mascot
1-D pre-fractionation^d	543	261	804
2-D pre-fractionation^e
Fr. 1 (pH 3–4.6)	268	123	391
Fr. 2 (pH 4.6-5.4)	393	178	571
Fr. 3 (pH 5.4-6.2)	370	139	509
Fr. 4 (pH6.2-7.0)	562	171	733
Fr. 5 (pH 7.0-10.0)	416	147	563
Total number^f	2009	758	2767
Total distinct proteins^g	1340	477	1817
Total distinct genes^h			1478

^aThe number of identified proteins with two or more peptide matches counted by using the non-redundant dataset of identified proteins. ^bThe number of identified proteins with one peptide match counted by using non-redundant dataset of identified proteins. ^cThe sum of the number of identified proteins with high confidence and low confidence as defined above. ^dGlomerular proteins were directly separated into 15 fractions by one-dimensional (1-D) SDS-PAGE. ^eGlomerular proteins were separated into 5 fractions with different pI ranges by solution-phase IEF in the first dimension and each fraction was further separated into 15 fractions by 1-D SDS-PAGE in the second dimension. ^fThe sum of the numbers of proteins identified in each fraction of 2-D pre-fractionation with high confidence or low-confidence as defined above. ^gThe sum of identified proteins counted by using the non-redundant dataset created by merging all the identified proteins in fractions of 1-D and 2-D pre-fractionation. ^hTotal distinct proteins included proteins derived from the same genes. In order to identify total distinct genes, the same gene symbols dispersed in the dataset were processed in an Excel work sheet to merge into one gene symbol by using the “Remove Duplicate” command.

ISSN: 1477-5956