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Transcripts Expressed in Malpighian Tubules of Female An. Stephensi

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Published: 10th Dec 2019

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Transcripts expressed in Malpighian tubules of female An. stephensi

In total, about 18,800 transcripts were identified in Malpighian tubules of adult female An. stephensi mosquitoes with an FPKM of ≥0.1. The total number of transcripts identified in Malpighian tubules was similar to that of ovaries and fat body tissue samples. The identified transcripts were transcribed from about 11,100 gene loci, with 7,883 transcripts similar to that of already annotated transcripts and about 8,000 spliced forms of transcripts from the annotated gene loci. In addition to these, additional 2,400 transcripts were found to be expressed in the Malpighian tubules from intergenic genomic loci not previously annotated. Out of the transcripts identified in the Malpighian tubules, 332 transcripts were found to be significantly differentially expressed in Malpighian tubules compared to other tissues. The significant differential expression was calculated based on the CuffDiff analysis with transcripts showing differential expression having a p-value of < 0.001. Among these, 318 were found to be upregulated significantly (≥2-fold), whereas only 14 transcripts were found to be significantly less expressed (≥2-fold) in Malpighian tubules when compared to other tissues. These Malpighian tubule enriched transcripts were found to be localized on the membranes and majority of them were found to possess transporter activity and hence involved in transmembrane transport (Figure 19). The list of top differentially expressed transcripts in Malpighian tubules is provided in the Table 3. Among these differentially expressed transcripts, 105 of them were previously annotated, 193 alternatively spliced forms and 34 transcripts were intergenic in nature.

Transcripts upregulated in Malpighian tubules compared to other tissues
Transcript ID VectorBase Gene ID FPKM Log2(fold change) Average p-value
MG MT Ov FB MT/MG MT/Ov MT/FB Average
ANSTF.4175.1 ASTEI04468 88.3 7855.1 23.7 137.0 6.5 8.4 5.8 6.9 0.000
ASTEI06726-RA ASTEI06726 23.9 1479.3 4.4 22.6 6.0 8.4 6.0 6.8 0.000
ANSTF.386.1 ASTEI00428 9.0 1425.5 5.4 18.3 7.3 8.0 6.3 7.2 0.000
ANSTF.8308.1 ASTEI08991 9.3 1278.0 5.4 21.8 7.1 7.9 5.9 7.0 0.000
ASTEI05155-RA ASTEI05155 9.7 598.8 2.2 6.6 5.9 8.1 6.5 6.9 0.000
ANSTF.284.4 ASTEI00312 2.9 379.0 1.1 4.8 7.0 8.4 6.3 7.2 0.000
ASTEI06449-RA ASTEI06449 4.3 359.5 0.8 5.3 6.4 8.9 6.1 7.1 0.000
ASTEI02758-RA ASTEI02758 2.4 310.2 1.9 4.9 7.0 7.4 6.0 6.8 0.000
ASTEI10959-RA ASTEI10959 2.1 289.6 1.2 3.1 7.1 8.0 6.6 7.2 0.000
ASTEI07579-RA ASTEI07579 2.2 211.2 0.5 2.0 6.6 8.6 6.8 7.3 0.000
ANSTF.6104.1 ANSTF.6104 2.0 203.4 1.1 2.7 6.7 7.5 6.3 6.8 0.000
ASTEI02654-RA ASTEI02654 3.7 198.9 0.4 3.1 5.7 9.0 6.0 6.9 0.000
ASTEI04060-RA ASTEI04060 1.6 198.6 0.8 2.9 7.0 8.0 6.1 7.0 0.000
ASTEI00901-RA ASTEI00901 0.8 184.6 0.2 0.9 7.8 9.6 7.7 8.4 0.000
ASTEI01700-RA ASTEI01700 1.5 128.4 0.5 2.2 6.4 7.9 5.9 6.7 0.000
ANSTF.1632.4 ASTEI01702 1.8 127.8 0.5 1.5 6.2 7.9 6.4 6.8 0.000
ANSTF.1630.1 ASTEI01700 1.0 121.9 0.4 1.9 7.0 8.4 6.0 7.1 0.000
ANSTF.1632.1 ASTEI01702 2.2 112.0 0.2 2.1 5.6 9.2 5.7 6.8 0.000
ASTEI08142-RA ASTEI08142 1.1 87.4 0.3 0.7 6.3 8.2 6.9 7.2 0.000
ANSTF.9906.1 ASTEI10709 1.2 83.1 0.2 1.1 6.1 8.7 6.2 7.0 0.000
ANSTF.284.3 ASTEI00311 0.5 81.4 0.3 0.9 7.5 8.0 6.4 7.3 0.000
ANSTF.5600.2 ASTEI06016 0.4 79.7 0.8 1.2 7.5 6.6 6.1 6.7 0.000
ANSTF.3991.1 ASTEI04280 0.6 71.8 0.2 1.5 6.8 8.7 5.6 7.0 0.000
ASTEI03454-RA ASTEI03454 0.4 70.8 0.3 1.7 7.5 8.1 5.4 7.0 0.002
ANSTF.1957.1 ASTEI02039 0.8 68.8 0.7 0.5 6.5 6.7 7.1 6.8 0.000
Transcripts downregulated in Malpighian tubules compared to other tissues
Transcript ID VectorBase Gene ID FPKM Log2(fold change) Average p-value
MG MT Ov FB MT/MG MT/Ov MT/FB Average
ASTEI11921-RA ASTEI11921 61.9 13.3 236.4 118.1 -2.2 -4.2 -3.2 -3.2 0.009
ASTEI09029-RA ASTEI09029 20.0 2.9 24.5 23.8 -2.8 -3.1 -3.0 -2.9 0.000
ANSTF.8907.3 ASTEI09638 23.3 1.4 8.6 12.8 -4.1 -2.6 -3.2 -3.3 0.000
ANSTF.6983.1 ANSTF.6983 9.8 2.2 13.8 15.7 -2.2 -2.7 -2.8 -2.6 0.000
ANSTF.330.1 ASTEI00365 13.6 0.4 4.0 2.3 -5.1 -3.4 -2.6 -3.7 0.000
ANSTF.10633.1 ASTEI11292 11.0 0.4 2.1 1.7 -4.7 -2.3 -2.1 -3.0 0.000
ANSTF.3653.1 ASTEI03910 7.0 1.5 7.2 6.6 -2.2 -2.3 -2.1 -2.2 0.006
ANSTF.10391.2 ASTEI11108 1.3 0.2 6.0 1.6 -2.6 -4.8 -2.9 -3.5 0.009
ANSTF.1801.1 ASTEI01871 2.7 0.3 1.4 5.2 -3.0 -2.1 -4.0 -3.0 0.000
ANSTF.5299.1 ASTEI05691 2.4 0.3 1.5 4.8 -2.8 -2.2 -3.8 -2.9 0.000
ANSTF.1019.1 ASTEI01094 0.9 0.2 3.7 0.9 -2.2 -4.2 -2.1 -2.9 0.000
ANSTF.8344.2 ASTEI09029 3.4 0.5 2.9 3.0 -2.7 -2.5 -2.5 -2.6 0.000
ASTEI01007-RA ASTEI01007 3.3 0.1 1.3 1.3 -5.9 -4.6 -4.6 -5.0 0.008
ANSTF.5392.1 ASTEI05791 0.6 0.1 1.2 1.0 -2.1 -3.1 -2.9 -2.7 0.002

 

Transcripts expressed in ovaries of An. stephensi

In ovaries of the adult female An. stephensi mosquitoes that were sugar fed, about 18,600 transcripts were identified with an FPKM of ≥0.1, corresponding to about 11,000 gene loci. Among these, about 8,000 transcripts were identical to the annotated transcripts and a similar number of transcripts were alternatively spliced forms of the annotated transcripts. Of these, 2,396 transcripts identified from the previously unannotated intergenic loci, considered as potentially novel gene transcripts. Among the total transcripts and transcript isoforms identified in ovaries, 1,588 transcripts were found to be significantly differentially expressed (≥2-fold) in ovaries when compared to the other tissues. The ovaries had the most number of unique transcripts that were not expressed in the other tissues. This probably is due to the fact that it is a more specialized organ and undergoes a lot of changes during the different stages of the female mosquito cycle. Of the 768 transcripts that were found to be significantly upregulated (≥2-fold), 291 of them were previously annotated in VectorBase while 386 were found to be alternatively spliced isoforms of the annotated transcripts and 91 were found to be from the previously unannotated gene loci. Among the 820 transcripts that were significantly less expressed (≥2-fold) in ovaries compared to other tissues, 341 were as previously annotated, 404 alternatively spliced forms and 75 from the unannotated intergenic genomic regions. The transcripts that were upregulated in ovaries were found to be involved mostly in processes such as microtubule-based movement, gene expression regulation, chromosome segregation and other processes of cell division and replication according to the gene ontology analysis (Figure 20). This shows that the ovaries when dissected were in the continued mode of development although the mosquitoes were fed only on sugars. The list of top 50 differentially expressed transcripts in ovaries is provided in the Table 4.

Transcripts upregulated in ovaries compared to other tissues
Transcript ID VectorBase Gene ID FPKM Log2(fold change) Average p-value
MG MT Ov FB Ov/MG Ov/MT Ov/FB Average
ANSTF.4289.1 ANSTF.4289 1.0 9.3 135.6 9.5 7.1 3.9 3.8 4.9 0.000
ANSTF.976.1 ASTEI01043 1.1 7.6 134.3 2.3 6.9 4.2 5.9 5.6 0.000
ASTEI01321-RA ASTEI01321 0.5 3.0 83.9 5.2 7.5 4.8 4.0 5.4 0.000
ANSTF.985.1 ASTEI01054 0.6 4.5 75.5 2.5 7.0 4.1 4.9 5.3 0.000
ASTEI10197-RA ASTEI10197 0.9 1.5 58.6 4.4 5.9 5.3 3.7 5.0 0.000
ANSTF.5853.1 ASTEI06270 0.6 4.6 54.0 1.6 6.4 3.6 5.0 5.0 0.000
ASTEI00287-RA ASTEI00287 0.6 1.5 46.5 0.9 6.3 5.0 5.7 5.7 0.000
ANSTF.28.3 ASTEI00038 1.0 2.1 46.4 0.7 5.6 4.5 6.0 5.3 0.000
ASTEI09747-RA ASTEI09747 0.8 1.6 43.9 0.9 5.9 4.8 5.6 5.4 0.002
ANSTF.4240.1 ASTEI04534 0.2 2.0 31.2 2.3 7.4 3.9 3.8 5.0 0.003
ANSTF.2463.2 ASTEI02597 0.2 0.8 26.9 1.4 6.8 5.0 4.3 5.4 0.000
ANSTF.6117.6 ASTEI06575 0.2 1.5 26.5 0.5 7.0 4.1 5.7 5.6 0.000
ASTEI02597-RA ASTEI02597 1.0 0.9 22.6 0.3 4.6 4.6 6.2 5.1 0.000
ANSTF.7908.4 ASTEI08579 0.1 1.5 19.7 1.4 8.1 3.7 3.8 5.2 0.007
ANSTF.7629.1 ASTEI08267 0.2 0.7 15.6 0.9 6.6 4.5 4.1 5.1 0.000
ANSTF.6292.1 ASTEI06764 0.1 0.7 12.2 0.5 6.5 4.1 4.6 5.1 0.000
ANSTF.2752.1 ASTEI02932 0.3 1.6 11.2 0.1 5.1 2.8 6.6 4.8 0.000
ANSTF.10761.2 ANSTF.10761 0.1 0.7 10.3 0.7 6.8 3.9 3.9 4.9 0.001
ANSTF.3857.3 ASTEI04130 0.2 0.5 10.3 0.2 5.7 4.5 5.9 5.3 0.000
ANSTF.279.1 ANSTF.279 0.1 1.0 9.6 0.6 7.2 3.3 3.9 4.8 0.000
ANSTF.6815.1 ASTEI07362 0.1 0.2 6.3 0.6 6.3 4.8 3.4 4.8 0.000
ANSTF.5523.3 ASTEI05928 0.1 0.2 5.4 0.4 6.0 4.8 3.9 4.9 0.001
ANSTF.2838.4 ASTEI03027 0.2 0.2 4.4 0.1 4.5 4.1 6.2 4.9 0.001
ANSTF.9079.1 ASTEI09826 0.2 0.2 3.3 0.1 4.3 4.3 5.8 4.8 0.000
ANSTF.280.1 ASTEI00304 0.0 0.0 1.0 0.1 5.3 5.4 4.0 4.9 0.008
Transcripts downregulated in ovaries of An. stephensi compared to other tissues
Transcript ID VectorBase Gene ID FPKM Log2(fold change) Average p-value
MG MT Ov FB Ov/MG Ov/MT Ov/FB Average
ANSTF.9066.1 ASTEI09812 2371.8 2399.8 540.3 2610.6 -2.1 -2.2 -2.3 -2.2 0.000
ASTEI01688-RA ASTEI01688 2098.0 1492.2 305.1 1250.0 -2.8 -2.3 -2.0 -2.4 0.000
ANSTF.5658.1 ASTEI06074 629.8 494.7 113.7 595.1 -2.5 -2.1 -2.4 -2.3 0.000
ANSTF.9189.1 ASTEI09954 560.1 430.6 104.0 449.4 -2.4 -2.1 -2.1 -2.2 0.000
ASTEI06555-RA ASTEI06555 507.9 373.2 90.7 376.2 -2.5 -2.0 -2.1 -2.2 0.000
ASTEI10810-RA ASTEI10810 470.3 249.2 59.8 242.1 -3.0 -2.1 -2.0 -2.4 0.000
ANSTF.8049.5 ASTEI08719 296.2 325.3 63.2 313.0 -2.2 -2.4 -2.3 -2.3 0.000
ASTEI04480-RA ASTEI04480 241.1 229.2 45.3 187.9 -2.4 -2.3 -2.1 -2.3 0.000
ASTEI00830-RA ASTEI00830 185.0 221.6 44.1 180.9 -2.1 -2.3 -2.0 -2.1 0.000
ASTEI00562-RA ASTEI00562 214.8 168.3 39.0 182.4 -2.5 -2.1 -2.2 -2.3 0.000
ANSTF.4718.1 ASTEI05068 192.0 181.6 40.6 163.9 -2.2 -2.2 -2.0 -2.1 0.000
ANSTF.6088.1 ASTEI06542 126.1 128.2 27.4 139.6 -2.2 -2.2 -2.3 -2.3 0.000
ASTEI09502-RA ASTEI09502 79.7 68.8 16.5 95.3 -2.3 -2.1 -2.5 -2.3 0.000
ASTEI03213-RA ASTEI03213 92.4 73.7 16.1 65.4 -2.5 -2.2 -2.0 -2.2 0.000
ANSTF.3517.1 ASTEI03784 76.2 37.4 9.3 37.5 -3.0 -2.0 -2.0 -2.4 0.000
ASTEI02887-RA ASTEI02887 72.3 49.1 12.2 56.4 -2.6 -2.0 -2.2 -2.3 0.000
ANSTF.4612.1 ASTEI04942 23.3 23.2 5.6 44.0 -2.1 -2.0 -3.0 -2.4 0.000
ANSTF.11624.1 ANSTF.11624 19.7 24.0 4.0 18.3 -2.3 -2.6 -2.2 -2.4 0.000
ASTEI04031-RA ASTEI04031 17.7 21.0 4.2 19.8 -2.1 -2.3 -2.2 -2.2 0.000
ANSTF.3510.1 ASTEI03778 11.6 18.0 2.8 11.7 -2.0 -2.7 -2.0 -2.2 0.000
ASTEI11442-RA ASTEI11442 14.6 15.0 3.0 13.7 -2.3 -2.3 -2.2 -2.2 0.000
ANSTF.3681.3 ASTEI03941 9.8 11.2 2.1 9.1 -2.3 -2.4 -2.2 -2.3 0.000
ANSTF.10338.2 ANSTF.10338 9.4 8.0 1.7 8.8 -2.5 -2.2 -2.4 -2.4 0.000
ASTEI07896-RA ASTEI07896 8.4 6.5 1.4 5.9 -2.6 -2.2 -2.1 -2.3 0.000
ANSTF.1076.1 ASTEI01148 1.2 0.9 0.2 0.9 -2.4 -2.0 -2.1 -2.2 0.002

Transcripts expressed in fat body of female An. stephensi

Total number of transcripts identified in fat body of adult female An. stephensi mosquitoes is 18,600 transcripts, similar to that of other three tissues. These transcripts identified with an FPKM of ≥0.1 and corresponded to 11,371 gene loci. A total of 8,015 annotated transcripts and 8,037 spliced isoforms were identified in fat body. About 2,398 transcripts identified in fat body were found to be transcribed from unannotated intergenic loci of the An. stephensi genome. Among the total number of transcripts identified in mosquito fat body, 425 were found to be significantly differentially expressed (≥2-fold) in fat body compared to other tissues. Of the 671 transcripts that were differentially expressed (≥2-fold), 569 were found to be significantly upregulated and 102 were found to be downregulated (≥2-fold) with p-values of <0.005. Among the upregulated transcripts, 238 of them were previously annotated in VectorBase while 287 were found to be alternatively spliced isoforms of the annotated transcripts and 44 were found to be from the previously unannotated gene loci. These upregulated transcripts were found to be localized mostly on the membranes and involved in metabolic processes such as fatty acid synthesis, chitin metabolism, transportation and calcium binding among others (Figure 21). Among the 102 transcripts that were significantly less expressed (≥2-fold) in ovaries compared to other tissues, 24 were as previously annotated, 73 alternatively spliced forms and 5 from the unannotated intergenic genomic regions. The list of top 50 differentially expressed transcripts in fat body is provided in the Table 5.

Transcripts upregulated in fat body compared to other tissues
Transcript ID VectorBase Gene ID FPKM Log2(fold change) Average p-value
MG MT Ov FB FB/MG FB/MT FB/Ov Average
ANSTF.7564.1 ASTEI08193 8.3 19.7 6.9 3969.1 8.9 7.7 9.2 8.6 0.000
ASTEI06560-RA ASTEI06560 9.4 13.6 5.7 2535.2 8.1 7.5 8.8 8.1 0.000
ASTEI10419-RA ASTEI10419 7.8 12.2 3.8 2149.3 8.1 7.5 9.2 8.2 0.000
ANSTF.5891.2 ASTEI06317 7.3 5.0 2.6 1738.4 7.9 8.4 9.4 8.6 0.000
ASTEI02267-RA ASTEI02267 4.9 11.1 3.2 1110.3 7.8 6.6 8.4 7.6 0.000
ANSTF.6103.1 ASTEI06565 2.9 6.1 1.6 906.6 8.3 7.2 9.1 8.2 0.000
ANSTF.6102.1 ASTEI06563 2.0 1.5 0.4 702.0 8.5 8.9 10.9 9.4 0.000
ANSTF.682.2 ASTEI00753 1.8 9.7 0.9 637.8 8.4 6.0 9.4 8.0 0.000
ASTEI08816-RA ASTEI08816 1.2 2.0 3.9 575.8 8.9 8.2 7.2 8.1 0.000
ANSTF.6181.3 ASTEI06644 0.1 3.4 2.5 485.4 12.1 7.2 7.6 8.9 0.000
ASTEI00591-RA ASTEI00591 1.7 5.7 1.0 446.1 8.1 6.3 8.8 7.7 0.000
ANSTF.7779.5 ASTEI08432 0.6 9.8 1.2 389.0 9.4 5.3 8.3 7.7 0.000
ANSTF.533.1 ASTEI00591 1.3 3.2 0.8 328.9 8.0 6.7 8.7 7.8 0.000
ASTEI05292-RA ASTEI05292 0.3 3.2 0.7 235.8 9.8 6.2 8.3 8.1 0.005
ANSTF.8488.1 ASTEI09198 0.7 4.2 0.4 230.8 8.4 5.8 9.2 7.8 0.003
ASTEI02389-RA ASTEI02389 0.8 4.0 0.3 189.8 7.9 5.6 9.4 7.6 0.001
ASTEI09946-RA ASTEI09946 0.9 1.4 0.3 148.8 7.4 6.8 9.0 7.7 0.000
ANSTF.8708.3 ASTEI09423 0.2 0.5 0.3 142.8 9.7 8.1 9.1 9.0 0.000
ANSTF.6627.1 ASTEI07156 0.3 1.6 0.3 131.3 8.7 6.3 8.9 8.0 0.000
ASTEI01256-RA ASTEI01256 0.5 0.6 0.3 116.0 7.9 7.7 8.5 8.0 0.000
ASTEI06585-RA ASTEI06585 0.3 1.3 0.4 112.4 8.4 6.5 8.0 7.6 0.000
ANSTF.5024.2 ASTEI05387 0.4 1.2 0.2 105.4 8.0 6.5 8.9 7.8 0.000
ANSTF.6965.4 ASTEI07518 0.7 0.6 0.3 98.2 7.1 7.4 8.5 7.7 0.000
ANSTF.854.1 ASTEI00923 0.2 1.0 0.1 78.1 8.3 6.3 9.0 7.9 0.000
ASTEI00609-RA ASTEI00609 0.2 0.2 0.2 52.7 8.1 7.9 8.1 8.0 0.000
Transcripts downregulated in fat body compared to other tissues
Transcript ID VectorBase Gene ID FPKM Log2(fold change) Average p-value
MG MT Ov FB FB/MG FB/MT FB/Ov Average
ASTEI09440-RA ASTEI09440 356.6 15.1 7.0 1.2 -8.3 -3.7 -2.6 -4.8 0.000
ASTEI09186-RA ASTEI09186 167.9 13.2 9.2 1.7 -6.7 -3.0 -2.5 -4.0 0.000
ASTEI00446-RA ASTEI00446 82.6 4.4 4.0 0.4 -7.6 -3.3 -3.2 -4.7 0.000
ANSTF.4550.1 ASTEI04872 62.3 17.0 5.6 0.9 -6.2 -4.3 -2.7 -4.4 0.000
ANSTF.5826.1 ASTEI06243 11.5 6.7 24.9 0.3 -5.4 -4.6 -6.5 -5.5 0.000
ANSTF.8000.5 ASTEI08666 16.2 23.1 8.6 0.8 -4.3 -4.8 -3.3 -4.1 0.000
ANSTF.5779.6 ASTEI06191 22.1 14.8 1.7 0.3 -6.3 -5.8 -2.7 -4.9 0.000
ANSTF.5428.2 ASTEI05828 21.1 15.0 8.1 0.7 -4.9 -4.4 -3.5 -4.3 0.000
ANSTF.1814.1 ANSTF.1814 17.4 3.2 5.0 0.3 -5.8 -3.4 -4.0 -4.4 0.001
ANSTF.5126.5 ASTEI05498 2.0 2.9 14.9 0.3 -2.8 -3.4 -5.7 -3.9 0.001
ANSTF.2567.5 ASTEI02716 14.6 1.2 3.4 0.1 -6.7 -3.2 -4.6 -4.9 0.004
ANSTF.5885.2 ASTEI06303 9.7 7.3 13.9 0.3 -5.2 -4.8 -5.7 -5.2 0.000
ASTEI10656-RA ASTEI10656 0.6 13.9 0.6 0.1 -3.0 -7.5 -3.1 -4.5 0.022
ANSTF.7823.5 ASTEI08487 9.0 7.3 12.6 0.3 -4.8 -4.5 -5.3 -4.8 0.000
ANSTF.5964.1 ASTEI06385 4.9 11.2 9.1 0.4 -3.7 -4.8 -4.5 -4.4 0.000
ANSTF.7131.3 ASTEI07716 4.0 2.4 11.0 0.2 -4.3 -3.6 -5.8 -4.6 0.013
ANSTF.4218.2 ASTEI04512 5.4 2.0 10.0 0.2 -4.7 -3.4 -5.6 -4.6 0.000
ANSTF.4701.1 ASTEI05048 8.2 2.8 3.5 0.1 -7.0 -5.5 -5.8 -6.1 0.003
ANSTF.1119.2 ASTEI01193 1.7 8.2 6.2 0.2 -3.1 -5.4 -5.0 -4.5 0.001
ANSTF.1516.1 ASTEI01574 4.6 7.6 8.1 0.4 -3.5 -4.2 -4.3 -4.0 0.000
ANSTF.9070.5 ASTEI09817 3.1 7.2 3.7 0.3 -3.6 -4.8 -3.9 -4.1 0.000
ANSTF.6051.1 ASTEI06494 6.7 1.8 3.7 0.2 -5.2 -3.3 -4.4 -4.3 0.000
ANSTF.10280.2 ASTEI11027 5.0 3.6 4.3 0.1 -5.4 -4.9 -5.2 -5.2 0.000
ASTEI02627-RA ASTEI02627 4.8 2.9 1.8 0.2 -4.8 -4.1 -3.4 -4.1 0.000
ANSTF.3503.3 ASTEI03768 2.8 2.5 1.3 0.1 -4.4 -4.2 -3.3 -4.0 0.000

 CHAPTER 4

Quantitative proteomics of An. stephensi

4.1. Introduction

Proteins are the functional units of a cell and hence form a very important component in the study and understanding of the functions of different genes. The functional differences between the cells and tissues and ultimately the organs can be attributed to the differences in the constituent proteins, in terms of the quantity and/or the quality. Therefore, proteomics – the large-scale study of proteins forms an essential complement to genomics and transcriptomics. Various aspects of gene functions are contributed by the post translational modifications, which can only be identified and studied at the protein level. We made an attempt to complement the differences between the mosquito tissues identified at the transcript level with that of the protein level differences as well as to provide a better understanding of the functions of these important mosquito tissues.

Proteomics have evolved as a very efficient tool to elucidate the global expression profiles of proteins, subcellular localizations and host-pathogen interactions. Global analysis of proteins and their expression profiles are the type of classic proteomic experiments that provides the basic framework of identification and quantification of components contributing to a particular disease state, tissue type, or physiological conditions. Several studies have been carried out to study the proteome of mosquito species, mainly Anopheles and Aedes. Proteome profiling of mosquito tissues varies in different physiological conditions such as different feeding states, upon infection and insecticide exposure and many studies have tried to elucidate these differences in expression in search of potential molecules that can be used in vector control. There have been several studies profiling the proteome profiles of mosquitoes and their tissues to gain insights in to the functional aspects of proteins expressed under different conditions. The protein profiling of fifteen adult mosquito tissues and parts was carried out in addition to the larval and pupal stages of An. stephensi providing protein level expression evidence to about 8,000 annotated proteins and 365 novel proteins that were missed, using mass spectrometry-based proteomics in [Prasad et al., 2017]. Salivary gland proteome have been studied by many groups considering the role of salivary glands in transmitting the vector-borne diseases [Dixit et al., 2011, Fontaine et al., 2012, Arca et al., 2017, Valenzuela et al., 2003, Vijay et al., 2014, Dhawan et al., 2017, Rawal et al., 2016]. Similarly, midgut is another mosquito organ of importance in the blood meal and parasite transmission and hence have been extensively studied by various groups under different physiological conditions [Fernandes et al., 2016, Games et al., 2016, Borges-Veloso et al., 2015, Cazares-Raga et al., 2014]. However, comparative proteomic studies among the mosquito tissues to decipher the tissue-specific proteins expressed in different mosquito tissues have been extremely rare. Hence, we present our effort to fill these lacunae in our understanding of the tissue specific protein expression of An. stephensi organs in this study.

Several methods are available for quantitative proteomics including labeled and label-free methods. Among the different labeling mechanisms, there are two types – in vivo labeling and in vitro labeling. In vivo labeling techniques includes Stable isotope labelling with amino acids in cell culture (SILAC) [Ong et al., 2002], stable isotope labeling with amino acids in mammals (SILAM) [Wu et al., 2004] and NeuCode (neutron encoding) SILAC [Rose et al., 2013]. Stable isotope incorporation methods introduce a small change in the mass of amino acids to peptides from different samples that can be distinguished at the MS1 level of data acquisition in mass spectrometer. The relative quantitation can then be calculated by the by comparing the abundance difference between heavy/light peptide pairs. These in vivo methods of labeling require the incorporation of stable isotope containing amino acids during the culture or growth stages of the cells or laboratory animals through labeled media/feed and hence is limited to cell culture or laboratory animals. However, the in vitro peptide labeling techniques are tags that can be added to the peptides at specific amino acid residues of peptides. Some of these labeling methods include isotope coded-affinity tags (ICAT), which involves the tagging of the thiol groups within the peptides with stable isotopes using the ICAT reagents [Aebersold, 2003], dimethyl labeling that labels the N-terminal residue and the lysine residue using formaldehyde [Hsu et al., 2003], isobaric mass tags and others. The isobaric tagging of the amino acids is a more versatile method that can provide quantitative expression information. Two techniques of isobaric mass tags namely, isobaric tags for relative and absolute quantification (iTRAQ), and tandem mass tags (TMT) are available and have been used extensively in quantitative proteomic studies. Since the overall mass of the tags for different labels are maintained constant, the peptides are eluted together at the MS1 level but upon fragmentation at the MS2 level, the individual labels are released. The relative abundance of the fragments of labels provide the abundance of the peptides in different samples.

Isobaric tags were first used for simultaneous identification and quantitation by Thompson et al. in 2003, in a study where they showed that peptides synthesized with tandem mass tags could be used for relative quantification in MS/MS experiments [Thompson et al., 2003]. Ross et al. then used the iTRAQ approach, to demonstrate the application with 4-plex to identify and compare the proteomes of yeast strains in 2004 [Ross et al., 2004]. An 8-plex version of the iTRAQ tags was used by Chloe et al. in 2007 to study the CSF proteins in Alzhiemer’s disease patients undergoing treatment [Choe et al., 2007]. Although TMT tags were first used to demonstrate the ability of quantification and identification in samples, the multiplexing ability and availability of iTRAQ preceded it’s use and application in studies. Multiplexing and improvement in the chemistry of TMT labels was seen much later after the introduction of multiplexing ability using tandem mass tags in 2008 by Dayon et al. [Dayon et al., 2008]. Until the introduction and demonstration of 8-plex ability of TMT in 2012 [Werner et al., 2012, Mcalister et al., 2012], iTRAQ labels were widely used by the community. Currently TMT offers better multiplexing ability with up to 10-fold multiplexing [Werner et al., 2014] compared to the 8-fold in iTRAQ. However, the mass differences between the TMT tags are incredibly small and hence was a limitation for use with the lower resolution powers of the earlier generation mass spectrometers. The tremendous improvement in the latest generation mass spectrometer resolutions have enabled a better use of this multiplexing ability using TMT.

The 4-plex iTRAQ, like other isobaric tags have a constant mass/charge of 145 Da. It comprises of three components – (i) the reporter ions which are of masses 114, 115, 116 and 117, (ii) a balancer group to accommodate the mass changes of the reporter ions ranging in mass from 24 – 31 Da to maintain the constant mass of 145 Da and (iii) an amine specific peptide reactive group, which reacts with the free amines at the peptide N-terminus and the epsilon amine group of Lysine residues as depicted in the Figure 18. The peptides from different samples to be studied are derivatized with different reporter ion tags, mixed together and analyzed in the mass spectrometer. Owing to the constant mass of the tags, the peptides labeled with different tags within the mixture elute simultaneously and are taken up for fragmentation. Upon fragmentation, the reporter ions are cleaved from the peptides to yield ions of different masses. The fragmentation pattern of the peptides is used for the peptide identification, while the intensity of the reporter ions represents the abundance of the specific peptide within each of the samples. The balancing groups are lost as neutral losses. Hence, the identification and the quantification information can be obtained from the spectra. Any interference of these reporter ions with the peptide fragment ions are minimized due to the lower mass range of these reporter ions. However, in the 8-plex reagents, the reporter ion of mass 120 is omitted owing to the interference due to immonium ion of phenyl alanine, which has the same mass. Figure 19 represents a typical spectrum showing the mass range of the 4-plex iTRAQ reporter ions within the peptide spectra. In this study, we have used the 4-plex iTRAQ-based labeling strategy to elucidate the variation in protein expression between the four mosquito tissues – midgut, Malpighian tubules, ovaries and fat body, that are involved in blood meal digestion.

4.2. Materials and methods

4.2.1. Mosquito rearing and dissection

Four female mosquito tissues – midgut, Malpighian tubules, ovaries and fat body were dissected under the stereo microscope from lab grown An. stephensi mosquitoes. The mosquitoes were grown under ambient conditions of ~70% humidity, temperatures ranging from 25 to 29°C and under a photoperiod:scotoperiod of 12:12 hours. About 500 mosquitoes were dissected to obtain sufficient amounts of proteins from each of the tissues. The dissected tissues were washed thoroughly in sterile phosphate buffered saline (PBS) to remove contaminants and other debris. The washed tissues were pelleted by centrifuging at 8,000 rpm, supernatant was removed and the tissue pellets were frozen for future use.

 

4.2.2. Protein extraction, sample preparation and iTRAQ labeling

Frozen tissue samples collected from adult mosquitoes were lysed in 0.5% SDS buffer and subsequently sonicated to disrupt the cells. The lysate was centrifuged at 14,000 rpm for 20 minutes at 4°C to remove cell debris.  The clear supernatant containing the total proteins was collected after centrifugation. Protein amounts were estimated in each of the tissue lysates using Bicinchoninic acid (BCA) assay and further confirmed by loading equivalent amounts of proteins on a polyacrylamide gel. Figure 20 shows the picture of the gel used for normalization of protein amounts. Twenty-five micrograms of protein based on BCA assay, was loaded on the gel from each of the tissue. Gel-based quantification of proteins was done based on 5ug of BSA as standard. About 80 µg of proteins from each tissue was processed for iTRAQ-based mass spectrometric analysis, post-SDS-PAGE normalization. Prior to trypsin digestion, the proteins from each tissue was reduced using 2 µL of tris-(2-carboxyethyl) phosphine (TCEP) at 60°C for 1 hour, to break the disulfide bridges and disrupt the secondary structures. Following this reduction, the cysteine residues were alkylated to prevent renaturation of hydrogen bonds, using methyl methanethiosulfonate (MMTS) for 10 minutes at room temperature. Alkylated protein samples were then digested with sequencing grade trypsin from Promega (Madison, WI. Cat#: V5111) in the ratio of 1 unit of enzyme to every 20 units of proteins at 37 °C, overnight. The volume of the digestion mixture was reduced to about 40 µL using the vacuum concentrator (Eppendorf AG, Hamburg). Concentrated peptides from each tissue were labeled with iTRAQ labeling reagents (Applied Biosystems, Cat#: 4352135) as per the manufacturer’s protocol. The tissue samples – midgut, Malpighian tubules, ovary and fat body were labeled with iTRAQ labels, to produce 114, 115, 116 and 117 reporter ions upon ionization in the mass spectrometer, respectively. The labeling reaction mixtures were quenched by the addition of milliQ water and labeling efficiency was calculated by pooling about 1 µL of the labeled peptides from each sample and analyzing the pooled mixture on the mass spectrometer. The labeling efficiency was determined by searching the raw files using iTRAQ modifications as dynamic modifications. The labeling efficiency of these peptides was found to be 99%.

 

4.2.3. Strong cation exchange chromatography (SCX)

The labeled peptides were pooled and dried using Vacufuge® vacuum concentrator (Eppendorf). The peptides were reconstituted with SCX solvent A containing 5 mM potassium phosphate buffer in 25% acetonitrile at pH 2.7. Reconstituted and labelled peptide mixture was fractionated based on their charge using a PolyLC strong cation exchange (SCX) liquid chromatography column (Cat#: 204SE0502). The dimension of the column used was 200 x 4.6 mm packed with polysulfoethyl A matrix of 200 Ǻ, 5 µm connected to Agilent 1200 infinity series HPLC. The separation of the peptide mixture was carried out using a gradient of increasing salt concentration of up to 350 mM KCl for a period of 50 minutes, as provided in Table 1. The eluate was collected in 96-well plate using a liquid handler. The fractions were then pooled manually, based on the chromatogram to obtain 23 fractions and dried in vacuum dryer to be reconstituted in 40 µL of 0.1% fluoroacetic acid. The salt content in the fractions were removed by a desalting process using the C18 (3M Empore high-performance extraction disks) stage-tips. The peptides bind to the C18 matrix, while the salts are washed off the column in multiple wash steps. The peptides are later eluted using 80% acetonitrile and dried and stored in -20 °C until the mass spectrometric analysis.

 

Table 6: Gradient used for SCX fractionation

Time (min) Solvent A (%) Solvent B (%) Flow rate (mL/min) Max. pressure (bar)
0.00 100 0 0.020 400
5.00 100 0 0.300 400
8.00 95 5 0.300 400
40.00 50 50 0.300 400
42.00 0 100 0.300 400
46.00 0 100 0.300 400
47.00 100 0 0.300 400
50.00 100 0 0.300 400

 

4.2.4. Mass spectrometry and data analysis

Twenty-three fractions after SCX fractionation were desalted using the C18 stage tips and analyzed on LTQ-Orbitrap Velos ETD mass spectrometer (Thermo Scientific, Bremen, Germany) interfaced with Easy-nanoLCII from Thermo Scientific (Bremen, Germany). Prior to analysis on the mass spectrometer, the peptides were enriched on a reversed phase liquid chromatography (RPLC) pre-column (2 cm, 5µ, 100 Ǻ) using 97% solvent A (0.1% aqueous formic acid). This was followed by resolution on the analytical column of about 12 cm, packed in-house with 3 µ, 100 Ǻ magic AQ C18 material (Michrom Bioresources Inc., Auburn, CA). The peptides were eluted from the column using a linear gradient of 5-30% solvent B (100% acetonitrile, 0.1% formic acid) over a period of 70 minutes at a constant flow rate of 0.35 µL/min. The eluting peptides were constantly sprayed on to the source using a nano electro spray emitter tip of 10 µ (New Objective, Woburn, MA). The spray voltage and heated capillary temperature were set to 2.0 kV and 220°C, respectively. Data acquisition was performed in a data dependent manner by selecting fifteen most intense precursor ions for fragmentation from each MS scan. MS and MS/MS scans were acquired in an Orbitrap mass analyzer at a resolution of 60,000 at 400 m/z and 15,000, respectively.

Data obtained from the mass spectrometer was searched against the protein database of An. stephensi Indian strain (version 2.2) released by VectorBase using Proteome Discoverer, version 2.0 (Thermo Fischer Scientific, Bremen, Germany) using SEQUEST and mascot search algorithms. The workflow consisted of a processing workflow consisting of spectrum selector, search algorithm nodes of SEQUEST HT and Mascot and a Target decoy PSM validator to generate the .msf files. The consensus workflow consisted of PSM grouper, peptide validator nodes, peptide and protein filter, protein scorer, protein grouping, Fido CT protein validator and peptide and protein quantifier nodes. Database search parameters included trypsin as the enzyme and a maximum of one missed cleavage was allowed in the peptide identification. Methylthiol modification of cysteine and iTRAQ labels at the peptide N-terminus and Lysine residues were specified as static modifications, while methionine oxidation was given as dynamic modification. A signal to noise ratio of 1.5 was defined for a precursor mass range of 350-10000 Da with 20 ppm and 0.05 Da mass tolerance for the precursor ion and fragment ions, respectively. A false discovery rate (FDR) of 1% was applied to the results at the peptide level and a minimum peptide length of 7 amino acids was used. The peptides identified in these searches were grouped into proteins and the reporter ion intensities of the unique peptides were used for the quantification.

4.3. Results

Mass spectrometry-based quantitative proteomic analysis of the four female mosquito tissues (midgut, Malpighian tubules, ovary and fat body) resulted in the identification of 3,372 proteins from 16,278 peptides. In total 84,733 PSMs were identified from a total of 1,10,616 spectra that were obtained from analysis of 23 fractions of the labeled samples on LTQ Orbitrap-Velos. The spectra obtained was searched against the VectorBase protein database of An. stephensi version 2.2 (ASTEI2.2) consisting of 11,789 An. stephensi proteins along with the addition of the common contaminants including Bovine Serum Albumin and trypsin. The total number of proteins identified in the four tissues was a union of proteins identified individually by two search algorithms, SEQUEST and Mascot. Of the 3,372 proteins identified, 3,168 proteins were found to be identified with high confidence, while 72 of them were of medium and 132 proteins were of low confidence scores. Hence, only the high confidence identifications of 3,168 proteins were considered for further analysis from this set. Of these, about 1000 proteins were found to be differential in total.

4.3.1. Differentially expressed proteins in midgut

Mosquito midgut marks the primary route of entry at the tissue level for the Plasmodium during an infected blood meal and forms the first line of barrier for their entry in the vector. Hence, it is a very important organ in malarial transmission. Even otherwise, with midgut being the primary digestive tract of the mosquito apart from the foregut and the hindgut, it is crucial to study the molecular composition of this mosquito tissue to gain insights into the functional roles of the tissue in addition to understanding the molecular basis of its components. These insights could prove extremely beneficial in targeting the crucial protein molecules that play an important role in the malarial transmission in case of infections. We identified a number of proteins that were differentially expressed in midgut when compared to other tissues. As summarized in Figure 23 (topmost diagonal box), 189 proteins were found to be significantly overexpressed (≥ 2-fold) and 73 proteins were found to be downregulated (≤ 2-fold) in midgut when compared to the other three tissues. Most of the proteins enriched in midgut were involved in proteolysis and carbohydrate metabolism, with a few of them in biomolecule transportation processes. Proteins that were downregulated in midgut compared to other tissues were mostly involved in translation along with other processes but did not show any significant enrichment of any particular class of proteins (Figure 28). The list of proteins that were found to be overexpressed in midgut are provided in Table 7.

 

Protein name # Peptides # PSMs # Unique Peptides Log2(Abundance ratios) Sequest HT score Mascot score
MG/MT MG/Ov MG/FB Average
Proteins overexpressed in midgut
1 ASTEI00991-PA 1 1 1 6.64 1.27 1.95 5.15 0.0
2 ASTEI04799-PA 1 2 1 4.6 5.67 4.4 5 6.1 105.1
3 ASTEI06640-PA 1 2 1 4.57 4.6 4.5 4.56 5.9 68.7
4 ASTEI10327-PA 3 14 3 4.45 4.75 4.32 4.52 37.7 281.5
5 ASTEI00445-PA 2 4 2 4.46 5.14 3.39 4.5 9.5 108.8
6 ASTEI11436-PA 3 12 3 3.95 4.48 4.89 4.49 26.2 206.2
7 ASTEI10274-PA 3 8 3 4.37 4.53 4.15 4.36 20.0 233.3
8 ASTEI04993-PA 2 9 2 4.59 4.41 3.85 4.32 13.6 115.7
9 ASTEI09453-PA 1 8 1 4.14 4.52 3.9 4.21 21.4 209.5
10 ASTEI10780-PA 1 2 1 4.23 3.88 4.34 4.16 3.9 51.4
11 ASTEI09440-PA 4 16 4 4.07 4.58 3.28 4.07 41 321.4
12 ASTEI08015-PA 1 14 1 3.77 4.17 3.43 3.82 22.7 188
13 ASTEI07506-PA 5 57 5 3.78 3.99 3.65 3.81 116.8 1020.8
14 ASTEI10118-PA 1 2 1 4.42 3.28 3.42 3.80 5.2 33.7
15 ASTEI06230-PA 7 20 6 3.81 3.84 3.74 3.80 40.1 276.4
Proteins downregulated in midgut
1 ASTEI10813-PA 1 2 1 -3.6 -3.8 -3.2 -3.5 4.5 80.8
2 ASTEI03929-PA 1 2 1 -4.3 -3 -2.5 -3.1 5.4 109.8
3 ASTEI00459-PA 1 2 1 -2.1 -4.7 -2.9 -2.9 5.3 49.6
4 ASTEI11554-PA 1 4 1 -3 -2.3 -2.7 -2.6 11.4 172.1
5 ASTEI09918-PA 2 6 2 -2.5 -2.6 -2.6 -2.6 14.5 96.8
6 ASTEI00003-PA 1 4 1 -2.4 -2.6 -2.6 -2.5 9.9 173.1
7 ASTEI04584-PA 1 2 1 -2 -2.8 -2.4 -2.4 4.6 65.9
8 ASTEI07745-PA 6 63 2 -1.6 -3.9 -2.3 -2.3 146.2 1140.2
9 ASTEI10165-PA 12 897 1 -2.6 -1.8 -2.4 -2.3 1782 11670
10 ASTEI11312-PA 1 4 1 -1.4 -3.2 -2.6 -2.2 11.1 144
11 ASTEI01490-PA 2 4 2 -2.4 -2.4 -1.7 -2.1 4.3 0.0
12 ASTEI11034-PA 1 8 1 -2.6 -2.4 -1.6 -2.1 18.8 121.7
13 ASTEI07273-PA 1 4 1 -2.4 -2.5 -1.5 -2 10.9 149.1
14 ASTEI09386-PA 5 25 5 -1.8 -2.4 -2 -2 45.445 407.34
15 ASTEI06310-PA 3 8 3 -2 -2.1 -2 -2 19.106 140.27

 

4.3.2. Proteins differentially expressed in Malpighian tubules

Malpighian tubules, along with the hindgut forms the excretory organs of mosquito. The tubules comprise mostly of single layered squamous cells with each tubules ranging in length from 2 – 70 mm and up to about 100µm in diameter [Phillips, 1981]. The tubules secrete a nearly isosmotic fluid containing Na+, Ca+ and Cl being the major ions, which are also transported by the tubules. The secretion of the fluid is accompanied by passive diffusion and selective secretion of certain solutes and toxins in to the lumen. Although some part of water and metabolite reabsorption occurs in the proximal tubules, majority occurs in the posterior hindgut and rectum. The mechanisms are so effective that they can reabsorb all of the water secreted producing highly concentrated excreta. Malpighian tubules have been reported to exhibit patterns of fluid and electrolyte secretion temporally at different stages. Reports of diuretic peptides influencing them in these processes have also been reported widely. Studies focusing on the mode of action of these excretory and transportation mechanisms have found the involvement of a number of regulated electrolyte transportation processes. Considering the role of these tubules in maintaining the homeostasis within the mosquito, it plays a very important role in the normal development, growth and reproduction. We noticed distinct expression patterns of 196 proteins in Malpighian tubules compared to that of the other tissues. Among these 152 proteins found to be overexpressed in Malpighian tubules were majorly found to be an integral part of the membrane and involved in the active transportation and in oxidation-reduction processes (Figure 29). Forty-four proteins that were found to be downregulated in Malpighian tubules did not show any significant enrichment of any particular class of proteins, although many of them were found to have a role in the replication and nucleotide metabolism related processes. A partial list of proteins differentially expressed in the Malpighian tubules are provided in the Table 8.

Protein name # Peptides # PSMs # Unique Peptides Log2(Abundance ratios) Sequest HT score Mascot score
MT/MG MT/Ov MT/FB Average
Proteins overexpressed in Malpighian tubules
1 ASTEI01144-PA 1 2 1 6.6 1.2 6.6 4.8 3.1 41.3
2 ASTEI10959-PA 2 4 2 3.8 4.2 3.9 4.0 6.1 67.9
3 ASTEI00788-PA 1 4 1 4.1 3.0 3.2 3.4 10.5 132.9
4 ASTEI10709-PA 2 4 2 3.2 3.1 3.6 3.3 10.9 122.2
5 ASTEI00311-PA 2 4 2 3.3 3.9 2.6 3.2 7.1 88.2
6 ASTEI00047-PA 5 26 5 3.1 3.2 3.4 3.2 51.5 353.3
7 ASTEI05225-PA 2 6 2 3.4 3.5 2.5 3.2 15.5 146.6
8 ASTEI08040-PA 2 4 2 2.4 3.5 3.4 3.1 7.9 93.3
9 ASTEI04467-PA 1 4 1 2.7 3.2 3.2 3.0 7.5 86.9
10 ASTEI05813-PA 14 101 14 2.8 3.0 2.9 2.9 233.3 1794.1
11 ASTEI00900-PA 5 16 5 2.9 2.6 3.2 2.9 36.0 193.5
12 ASTEI03993-PA 2 10 2 3.4 2.5 2.8 2.9 26.9 336.7
13 ASTEI02758-PA 7 42 7 2.9 3.1 2.6 2.9 110.9 605.3
14 ASTEI03793-PA 9 42 9 2.3 3.2 3.1 2.9 95.6 561.0
15 ASTEI08358-PA 6 24 6 2.8 3.1 2.6 2.9 54.2 381.7
Proteins downregulated in Malpighian tubules
1 ASTEI00991-PA 1 1 1 -6.6 -6.6 -6.6 -6.6 0.0
2 ASTEI01199-PA 2 3 2 -6.6 -6.6 -6.6 -6.6 2.7 38.7
3 ASTEI09883-PA 2 4 2 -3.3 -2.0 -3.3 -2.9 10.6 122.7
4 ASTEI03583-PA 1 2 1 -1.3 -3.4 -3.7 -2.8 5.5 62.4
5 ASTEI00611-PA 2 12 2 -3.1 -2.3 -2.4 -2.6 16.0 81.0
6 ASTEI00275-PA 4 21 4 -2.6 -2.7 -1.4 -2.2 42.9 293.4
7 ASTEI10118-PA 1 2 1 -4.4 -1.1 -1.0 -2.2 5.2 33.7
8 ASTEI01638-PA 1 2 1 -2.6 -1.7 -1.8 -2.0 4.3 41.3
9 ASTEI05146-PA 1 2 1 -2.7 -1.8 -1.4 -2.0 2.2 0.0
10 ASTEI00858-PA 2 4 2 -2.5 -1.4 -1.7 -1.9 6.7 20.8
11 ASTEI10954-PA 1 2 1 -2.1 -1.2 -2.2 -1.8 2.5 17.8
12 ASTEI10803-PA 7 124 2 -2.3 -1.6 -1.5 -1.8 167.8 892.9
13 ASTEI02661-PA 1 4 1 -2.1 -1.6 -1.6 -1.8 11.0 157.3
14 ASTEI07837-PA 3 6 3 -2.0 -1.4 -1.8 -1.7 9.4 52.2
15 ASTEI02635-PA 1 4 1 -1.7 -1.7 -1.7 -1.7 7.8 44.5

4.3.3. Differentially expressed proteins in ovaries

Ovaries are one among the two-primary female mosquito reproductive organs, the other being fat body. A pair of ovaries held by individual oviducts that fuses into a common one is present towards the posterior region of the adult mosquito. Blood-meal is an essential prerequisite for the maturation of ovaries and for vitellogenesis. The nutrients from the blood meal are utilized for these processes. Understanding of the proteins and differences in molecular components of these specialized organs are crucial in controlling the growth of mosquito populations. Developmental stages of the ovaries are represented by the posterior movement of the oocyte within tubular structures called ovarioles, with the most developed oocytes at the base, towards the oviduct. Post-maturation, the developed oocytes enter the oviduct to allow for the development and expansion of the next oocytes within the ovarioles. Vitellogenesis or the accumulation of the egg yolk proteins form the major source of nutrients for the developing embryo. Oocytes take up the vitellogenins produced by the fat body into the hemolymph by endocytic mechanisms mediated by specific receptors. We found that the proteome of ovary was significantly different from that of the other organs with about 375 proteins that were significantly differentially expressed of the 3,168 high confident proteins identified in the study. Of these, 302 proteins were found to be significantly overexpressed (≥ 2-fold) in ovaries compared to the other three tissues, while 73 of them were found to be significantly less-expressed. The proteins enriched in the ovaries corresponded mostly to the intracellular proteins majorly located in the ribosomes and nuclear compartments, as against the membrane component proteins in midgut and Malpighian tubules (Figure 30). This is in agreement with the physiological and functional differences of these tissues in the mosquito. The proteins that were overexpressed in ovaries compared to other tissues were involved mostly in translation, transcription and DNA replication and repair processes. As expected, these proteins were found to be downregulated in other tissues, especially in midgut and Malpighian tubules. Interestingly, membrane component proteins and those that are known to be involved in redox processes, proteolysis and other metabolic processes were significantly downregulated in ovaries compared to the other tissues. Table 9 provides a partial list of proteins that were differentially expressed in ovaries compared to the other three tissues.

  Protein name # Peptides # PSMs # Unique Peptides Log2(Abundance ratios) Sequest HT score Mascot score
Ov/MG Ov/MT Ov/FB Average
Proteins overexpressed in ovaries
1 ASTEI00958-PA 1 4 1 6.6 6.6 6.6 6.6 6.5 16.1
2 ASTEI01777-PA 4 8 3 6.6 6.6 6.6 6.6 14.8 85.9
3 ASTEI03531-PA 1 2 1 6.6 6.6 6.6 6.6 2.6 15.7
4 ASTEI05695-PA 2 6 2 1.2 6.6 6.6 4.8 10.9 116.5
5 ASTEI06262-PA 1 2 1 6.6 6.6 1.6 5.0 5.8 32.8
6 ASTEI10733-PA 5 18 5 4.2 4.1 3.0 3.8 47.7 516.0
7 ASTEI05877-PA 2 2 2 3.8 3.1 3.0 3.3 2.5
8 ASTEI00459-PA 1 2 1 4.7 2.6 1.8 3.1 5.3 49.6
9 ASTEI02829-PA 2 4 2 3.3 3.4 2.3 3.0 6.8 47.0
10 ASTEI02129-PA 4 16 4 3.3 3.2 2.6 3.0 40.2 316.2
11 ASTEI11343-PA 1 2 1 2.9 2.6 3.0 2.9 4.3 42.7
12 ASTEI01381-PA 2 5 2 2.4 3.5 2.6 2.8 11.0 140.3
13 ASTEI01321-PA 25 240 25 2.9 3.1 2.5 2.8 589.4 4160.3
14 ASTEI01382-PA 5 22 5 2.8 2.9 2.7 2.8 47.0 388.3
15 ASTEI10087-PA 1 6 1 2.9 2.8 2.5 2.7 12.1 37.7
Proteins downregulated in ovaries
1 ASTEI02928-PA 1 2 1 -4.1 -3.0 -1.2 -2.8 2.7 38.4
2 ASTEI11700-PA 3 38 1 -3.9 -1.4 -2.7 -2.7 71.5 510.4
3 ASTEI04799-PA 1 2 1 -5.6 -1.1 -1.3 -2.7 6.1 105.1
4 ASTEI08189-PA 1 2 1 -2.7 -2.2 -3.1 -2.6 2.5 56.8
5 ASTEI11276-PA 17 517 2 -2.7 -1.0 -3.9 -2.5 1095.0 8233.5
6 ASTEI03850-PA 1 2 1 -3.9 -1.1 -2.6 -2.5 3.3 24.3
7 ASTEI04729-PA 2 6 2 -2.1 -3.4 -1.8 -2.5 15.4 152.9
8 ASTEI00886-PA 4 14 4 -3.5 -2.3 -1.3 -2.3 29.3 229.0
9 ASTEI10317-PA 1 2 1 -2.5 -1.9 -2.6 -2.3 4.0 51.6
10 ASTEI10660-PA 2 5 2 -2.1 -1.4 -3.4 -2.3 8.6 52.0
11 ASTEI10756-PA 3 10 3 -1.8 -3.1 -2.1 -2.3 18.2 117.4
12 ASTEI00536-PA 3 11 3 -2.8 -2.8 -1.3 -2.3 22.6 203.0
13 ASTEI05529-PA 1 2 1 -3.6 -1.2 -1.8 -2.2 4.1 65.5
14 ASTEI03045-PA 5 18 5 -3.0 -1.1 -2.3 -2.1 43.6 319.7
15 ASTEI09499-PA 2 4 2 -3.9 -1.2 -1.2 -2.1 7.0 52.6

4.3.4. Differentially expressed proteins in fat body

Fat body is an important dynamic tissue, which is distributed throughout the mosquito body covering the gut and reproductive organs and plays a key role in the energy storage and utilization in addition to various metabolic processes. The fat body is akin to the liver tissue in function but is composed of loose tissue mainly composed of adipose cells. They store lipids as the major energy reservoir along with the glycogen that is metabolized to supply the energy needs for the flight and intermittent periods of starvation during metamorphosis [Arrese et al., 2001]. It is the site of synthesis of hemolymph proteins and metabolites. Proteins involved in storage, metabolism and vitellogenesis are known to be expressed in fat body. Being the site of mosquito’s intermediary metabolism, fat body should be able to integrate signals from other parts of the mosquito. Most of these interactions are known to be hormone-mediated which necessitates the mosquito fat body to receive and respond to these signals [Arrese and Soulages, 2010]. We noticed a total of 165 proteins to be differentially expressed in fat body compared to the other tissues. Of these, 149 proteins were found to be overexpressed in fat body. Majority of these proteins were part of processes such as oxidation-reduction, glycogen metabolism, carbohydrate and other metabolic processes (Figure 31). The sixteen downregulated proteins were found to have a role in transport along with others. The partial list of fat body differentially expressed genes are provided in Table 10.

  Protein name # Peptides # PSMs # Unique Peptides Log2(Abundance ratios) Sequest HT score Mascot score
FB/MG FB/MT FB/Ov Average
Proteins overexpressed in fat body
1 ASTEI03317-PA 1 4 1 6.4 5.1 5.4 5.6 9.5 171.6
2 ASTEI09699-PA 2 4 2 6.6 2.2 6.6 5.1 8.1 53.0
3 ASTEI02890-PA 1 6 1 5.0 5.3 4.7 5.0 16.7 222.3
4 ASTEI06317-PA 4 14 4 4.7 4.9 4.4 4.7 26.6 264.5
5 ASTEI05746-PA 2 6 2 4.0 4.5 3.3 3.9 16.3 70.1
6 ASTEI02077-PA 3 44 2 3.5 4.1 3.7 3.8 98.3 1163.4
7 ASTEI07953-PA 4 16 4 3.7 3.4 4.0 3.7 25.6 252.4
8 ASTEI06560-PA 2 34 2 3.5 3.2 3.6 3.4 83.9 696.6
9 ASTEI10682-PA 5 24 5 2.8 3.2 4.0 3.3 45.4 402.0
10 ASTEI07956-PA 5 34 5 3.4 3.2 3.3 3.3 69.0 603.7
11 ASTEI02079-PA 5 82 5 2.9 3.4 3.3 3.2 231.2 2441.7
12 ASTEI01820-PA 1 2 1 3.2 3.5 3.0 3.2 4.3 54.4
13 ASTEI08078-PA 5 50 5 2.8 3.4 3.2 3.1 111.9 825.1
14 ASTEI03062-PA 4 8 3 3.1 3.2 3.1 3.1 16.9 108.7
15 ASTEI07954-PA 4 37 4 2.9 2.7 3.5 3.1 92.3 769.1
Proteins downregulated in fat body
1 ASTEI09776-PA 1 2 1 -6.6 -6.6 -6.6 -6.6 3.4 32.0
2 ASTEI05312-PA 2 4 2 -3.4 -2.2 -2.6 -2.7 8.6 77.3
3 ASTEI05408-PA 1 24 1 -3.0 -3.1 -1.7 -2.6 58.5 301.5
4 ASTEI03783-PA 3 10 1 -3.2 -2.2 -2.1 -2.5 9.8 94.2
5 ASTEI10513-PA 2 14 2 -2.8 -1.8 -2.4 -2.3 45.4 334.6
6 ASTEI00630-PA 1 2 1 -3.1 -1.8 -1.4 -2.1 3.1 37.5
7 ASTEI09049-PA 1 2 1 -1.8 -1.6 -2.9 -2.1 3.2 23.8
8 ASTEI08241-PA 1 2 1 -1.6 -2.1 -2.0 -1.9 5.6 82.6
9 ASTEI09449-PA 2 4 2 -3.0 -1.0 -1.4 -1.8 9.4 174.2
10 ASTEI06279-PA 3 16 1 -2.3 -1.5 -1.3 -1.7 25.0 252.8
11 ASTEI03093-PA 2 4 2 -2.0 -1.1 -2.0 -1.7 8.5 67.5
12 ASTEI07253-PA 3 14 3 -1.4 -1.7 -1.7 -1.6 35.6 281.8
13 ASTEI06369-PA 1 2 1 -2.0 -1.3 -1.5 -1.6 5.3 38.3
14 ASTEI07720-PA 2 4 2 -1.3 -1.3 -1.9 -1.5 8.3 53.7
15 ASTEI05989-PA 6 24 6 -1.5 -1.4 -1.1 -1.3 63.0 541.0

The proteins enriched in these organs, especially, midgut and fat body are known to play a significant role in influencing the rate of parasitic infection (either enhance or inhibit the parasitic growth) in the vector host. We have compiled a list of the proteins that enhance or inhibit the plasmodium infection at various stages of their life-cycle in different mosquito tissues such as midgut, hemolymph and salivary glands in study by literature survey. The information on the infection-associated mosquito proteins have been mostly from studies performed in An. gambiae, which has been published in Malaria Journal and highly accessed [Sreenivasamurthy et al., 2013]. The list of proteins along with other functionally relevant aspects of the An. gambiae orthologs in An. stephensi, with their expression at RNA and protein levels is provided in the next chapter.

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