Expression and Functional Sialome of Triatomines, Insect Vectors of Chagas Disease

University of Texas at El Paso ScholarWorks@UTEP

Open Access Theses & Dissertations

2020-01-01

Expression And Functional Sialome Of Triatomines, Insect Vectors Of Chagas Disease

Maria Tays Mendes University of Texas at El Paso

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This is brought to you for free and open access by ScholarWorks@UTEP. It has been accepted for inclusion in Open Access Theses & Dissertations by an authorized administrator of ScholarWorks@UTEP. For more information, please contact [email protected]. EXPRESSION AND FUNCTIONAL SIALOME OF TRIATOMINES, INSECT VECTORS OF CHAGAS DISEASE

MARIA TAYS MENDES

Doctoral Program in Bioscience

APPROVED:

Igor C. Almeida, D.Sc., Chair

Douglas Watts, Ph.D.

Katja Michael, Ph.D.

______Siddhartha Das, Ph.D.

______Rosa A. Maldonado, D.Sc., Advocate

Stephen L. Crites, Jr., Ph.D. Dean of the Graduate School

by Maria Tays Mendes 2020

Dedication

To my family, especially to my husband, Leandro, my kids Luis and Emily, and to my grandmother (in memoriam). Before I left my country to start this journey, my grandmother gave me some money, which I refused at first because I knew it would be more useful for her. She made me accept it anyways, and told me it would mean a lot to her because once I reached the end, she could tell everyone that she helped me get there. Unfortunately, she passed away a year before that. Thank you “vó Quinquinha”, I dedicate this work to you. I will love you forever. EXPRESSION AND FUNCTIONAL SIALOME OF TRIATOMINES, INSECT VECTORS OF CHAGAS DISEASE

MARIA TAYS MENDES, M.Sc.

DISSERTATION

Presented to the Faculty of the Graduate School of The University of Texas at El Paso in Partial Fulfillment of the Requirements for the Degree of

DOCTOR OF PHILOSOPHY

Department of Biological Sciences THE UNIVERSITY OF TEXAS AT EL PASO May 2020

Acknowledgements

My sincere thanks:

To my mentor Dr. Igor Almeida for giving me the opportunity to be part of his group and for all the support he has given to me so far.

To my committee members Dr. Siddhartha Das, Dr. Katja Michael, and Dr. Douglas Watts for their support and insights into my project.

To my advocate Dr. Rosa Maldonado for her encouragement and kind words.

To all the present and past Almeida’s lab members, faculty, staff and core facilities for their assistance along the years. Specially thanks to Nasim Karimi, Susana Portillo, Brian Grajeda,

Igor Estevao, Cameron Ellis, Uriel Ortega, Nuria Cortes, Brenda Zepeda, Gloria Polanco, Ramon

Brito, and Emanuella Fajardo.

To all the professors of the Department of Biological Sciences for all the teachings and experiences transmitted.

To colleagues and former colleagues of the Graduate School for their excellent coexistence, for their help during the disciplines, for the moments of relaxation, for the scientific discussions and exchange of experiences. Special thanks to those who helped me to correct this dissertation.

To my former advisor Dr. Carlo José Freire de Oliveira for the trust placed in me and for the help not only in my scientific development but also in my personal growth.

To the collaborations made so far: Dr. Carlo José Freire de Oliveira and his lab members for providing the saliva samples; Dr. José Marcos Ribeiro for sharing the P. herreri database; Dr.

Luis Fabiano Oliveira, for the BLAST analysis; Dr. Laura-Isobel for the metabolomic analysis;

Dr. Alan Carneiro for teaching me the Toll-like receptors assays; Dr. Douglas Watts, Dr.

Belkisyolé Alarcón De Noya, Dr. Oscar Noya, Dr. Iliana R. Malo, Dr. Janine M. Ramsey, Dr. Léa

v S. Soussumi, Dr. Faustino Torrico, Dr. Maria Paola Zago, Dr. Julio Alonso-Padilla, Dr. Luis

Izquierdo, Dr. Maria-Jesus Pinazo, Dr. Joaquim Gascon for providing the human sera pools from

Chagas disease patients (ChHSP) and normal human sera pool (NHSP).

To my dear friends Sol (Soraia), Monica, and Luciene for the great moments lived together.

Additionally, to my friends in Brazil Tamires, Marcos, Monique, and Lara for the comfort given by the long Skype talks. Thank you for allowing me to be a part of your lives.

To all my family members for their encouragement and understanding. In particular, to my parents, Terezinha and João Pedro, for always supporting and believing in me. To my husband,

Leandro and my kids, Luis Felipe and Emily for their patience and love. To my parents-in-law,

Susana and Edson, and my sister-in-law Thamyres for making this journey happier. To my whole family in Brazil who despite the distance did not stop supporting me.

To the funding agencies, the Science Without Borders program by the Coordination for the

Improvement of Higher Education Personnel (CAPES), Brazil, the Border Biomedical Research

Center (BBRC), and the National Institutes of Health (NIH).

To everyone who directly or indirectly helped in the execution of this work.

Finally, to God, for the gift of life and the opportunities offered.

vi Abstract

Triatomines are blood-sucking arthropods that transmit Trypanosoma cruzi, the etiologic agent of

Chagas disease (ChD). Triatomines use bioactive molecules in the saliva for successful blood feeding and to evade the hemostatic and immune defense system of the hosts. Knowing the saliva composition could be useful for a better understanding which and how insect-derived molecules might influence host-parasite interactions. Previous studies have shown that some saliva-derived proteins and lipids can modulate the host immune system and increase T. cruzi infection. We hypothesize that the triatomine saliva contains a great diversity of lipids and proteins that can modulate the mammalian host immune response favoring blood-feeding and pathogen transmission. Moreover, these molecules could be used as biomarker of vector bite. Thus, the main purpose of this work is to conduct an omics (proteomic, lipidomic, and metabolomic) analysis on the saliva of different species of triatomines and identify these potential molecules. To address our hypothesis, we first identified the proteins, lipids, and metabolites (Specific Aim 1), and then tested the immunoreactivity against sera of negative or positive ChD patients (Specific Aim 2). Saliva of two species from North America, Meccus pallidipennis and Triatoma lecticularia, and two from

South America, Panstrongylus herreri and Rhodnius prolixus, were obtained by dissection of the triatomine salivary glands. The proteins were digested using a Filter-Aided Sample Prep (FASP) kit. Extracellular vesicles (EVs) were recovered in the triatomine saliva after ultrafiltration. The lipids and metabolites were extracted by Folch’s partition. Resulting peptides, lipids and metabolites were analyzed by high-resolution liquid chromatography-tandem mass spectrometry

(HR-LC-MS/MS) in a QE-Plus Orbitrap mass spectrometer. Immunoreactivity against sera of negative or positive ChD patients was screened by chemiluminescent enzyme-linked immunosorbent assay (CL-ELISA). Significant qualitative and quantitative differences were

vii observed at protein, lipid, and metabolite levels between the four-triatomine species. No clustering regarding geographical origin was noticed; however, considerable differences were observed regarding the tribes of the four triatomine species analyzed. The most abundant proteins in triatomine saliva belong to the lipocalin group. EVs were found for the first time in the triatomine saliva. Different immunoreactivity against salivary antigens with ChD sera from different countries was found. Eighteen lipid classes were identified in the triatomine saliva, including the lyso-phosphatidylcholine (LPC)-C16:0 previously described. Arachidonic acid (C20:4), the precursor of prostaglandins, and some purines such as adenosine, were also detected. In conclusion, our findings will further our understanding of potential effects of triatomine saliva in the establishment and long-term maintenance of T. cruzi infection within the mammalian host.

Keywords: Triatomines; Saliva; Proteomics; Lipidomics; Metabolomics, Chagas Disease.

viii Table of contents

Acknowledgements ...... v

Abstract ...... vii

Table of contents ...... ix

List of tables ...... xi

List of figures ...... xii

Chapter 1: General introduction...... 1 1.1 Chagas disease and Trypanosoma cruzi ...... 1 1.2 Triatomines ...... 3 1.3 Hematophagy and biomolecules present in saliva ...... 7 1.4 Significance, hypothesis and specific Aims...... 10

Chapter 2: In-depth high-resolution proteomic analysis of triatomines saliva from distinct geographical locations reveals substantial differences in their proteome profiles and immunoreactivity ...... 14 2.1 Introduction ...... 14 2.2 Materials and methods ...... 16 2.3 Results ...... 24 2.4 Discussion ...... 50

Chapter 3: Triatomine saliva lipidomic and metabolomics: identification of non-protein compounds with possible immune effect in the mammalian host ...... 56 3.1 Introduction ...... 56 3.2 Materials and methods ...... 58 3.3 Results ...... 63 3.4 Discussion ...... 83

Chapter 4: Final conclusions and future directions ...... 87 4.1 Overview and final conclusions ...... 87 4.2 Future directions ...... 90

ix References ...... 92

Appendix ...... 106 List of abbreviations ...... 106 Triatomines: laboratory maintenance and saliva collection ...... 110 List of publications and manuscripts ...... 114

Curriculum vitae ...... 118

x List of tables

Table 2.1. Number of protein found in the total triatomine saliva...... 46

Table 2.2. Percentage of functional classification of the housekeeping proteins...... 47

Table 2.3. Major proteins (top 10) found in each species of triatomine...... 48

Table 3.1. Summary of number of lipid identified...... 81

xi List of figures

Figure 1.1. Trypanosoma cruzi life cycle...... 12

Figure 1.2. Triatomine species chosen for this study and their geographical distribution...... 13

Figure 2.1. Schematic representation of the methodology used...... 39

Figure 2.2. Proteomic analysis of the total saliva from the four triatomine species...... 41

Figure 2.3. Heatmap representation of secreted proteins...... 42

Figure 2.4. UF-sal and FT-sal analysis from the four different triatomine species...... 43

Figure 2.5. Sera from Chagas human sera pool (ChHSP) patients from different countries presents different immune response against salivary antigens from the different triatomines. .... 44

Figure 2.6. Immunoreactivity of ChD human serum pools against salivary antigens from different triatomines...... 45

Figure 3.1. Schematic representation of the methodology used for extraction...... 68

Figure 3.2. Comparison between the organic phases from four different triatomine species in positive- (A) and negative-modes (B)...... 69

Figure 3.3. Total ion chromatogram (TIC) of aqueous phase in positive- (A) and negative-modes

(B)...... 70

Figure 3.4. Principal component analysis (PCA) of identified lipids and principal coordinate analysis (PCoA) of metabolites in positive- and negative-modes...... 71

Figure 3.5. Comparison of the lipid classes percentage identified by MS-Dial between the different triatomine species...... 72

Figure 3.6. Molecular structures of lyso-PLs identified in this study...... 74

Figure 3.7. Lysophospholipids identified in the triatomine saliva in positive- and negative- modes...... 75

xii Figure 3.8. Arachidonic acid (C20:4) identification in negative mode...... 76

Figure 3.9. Identification of very-long chain fatty acids (C28:7) in the triatomine saliva...... 77

Figure 3.10. Comparison of the metabolic features identified in the triatomine saliva...... 78

Figure 3.11. Molecular network of the purines identified in the triatomine saliva...... 79

Figure 3.12. Identification of purines in triatomine saliva...... 80

xiii Chapter 1: General introduction

1.1 CHAGAS DISEASE AND TRYPANOSOMA CRUZI

Chagas disease (ChD) is a parasitic disease caused by the protozoan, Trypanosoma cruzi.

ChD is one of the top five neglected tropical diseases, present mainly in Latin American countries, affecting 6-8 million people worldwide (Perez-Molina and Molina 2018). It is a potentially fatal disease, and around 10,000 people may die of complications per year (WHO 2010). The number of cases of ChD has increased in nonendemic areas such as in Australia, Japan, and the United

States due to the growth of migration from endemic countries (Perez-Molina, Norman et al. 2012).

Currently, in the U.S.A., it is estimated that 300,000 individuals are chronically infected with T. cruzi (Schmunis).

The routes of infection include the vector feces, ingestion of contaminated food, congenital transmission, blood transfusion and organ transplantation (Combs, Nagajyothi et al. 2005, Coura and Borges-Pereira 2010, Rassi, Rassi et al. 2010, Gourbiere, Dorn et al. 2012). Most vectors of

ChD defecate while blood-feeding on the host and release the infective metacyclic trypomastigote forms with the excrements, which can gain access to the host through the injured skin or inoculation into the exposed oral or ocular mucosal membranes. Besides the metacyclic trypomastigote form, T. cruzi exhibits a life-cycle with three other distinct developmental stages, two proliferative forms: (i) epimastigote, which is inside the vector’s midgut, and (ii) intracellular amastigote, which is inside the mammalian host cells; and another infective form: (iii) the circulation bloodstream trypomastigotes, which can be ingested by a triatomine vector, and start a new natural life cycle (Fig. 1.1).

1 ChD has two stages or phases: the acute and chronic phases. The disease can vary between no symptoms to severe disease and sometimes even death. The acute phase has a very high parasitemia. The chronic phase is further subdivided into asymptomatic (or indeterminate) and symptomatic phases. As the name implies, the indeterminate stage does not exhibit any clear clinical manifestation(s) of infection and may last many years or a lifetime; it happens in 70-80% of the patients with ChD. On the other hand, the symptomatic chronic phase occurs in 20-30% of patients and is characterized by cardiovascular disease, which leads to congestive cardiac failure and sudden cardiac death, and/or gastrointestinal (GI) complications, such as megacolon or megaesophagus (Schmunis 2007, Custer, Agapova et al. 2012, Perez-Molina, Norman et al. 2012).

At present, ChD treatment includes only two drugs: nifurtimox [Lampit®, Bayer; 5- nitrofuran 3-methyl-4-(5’-nitrofurfurylideneamine) tetrahydro-4H-1,4-tiazine-1,1-dioxide] and benznidazole (Rochagan®, Radanil®, Roche; N-benzyl-2-nitroimidazole acetamide) (Coura

2002, Maya, Bollo et al. 2003, Urbina 2009). These drugs induce several severe side effects, which may result in discontinuation of treatment in 20-30% of patients. Furthermore, there is no vaccine and the diagnostic tests need to be improved due to the high genetic variability of the parasite.

Taken together, all these facts make the management of ChD difficult and complex.

2 1.2 TRIATOMINES

Triatomines are hematophagous insects of great medical, social and economic relevance.

They belong to the class Insecta, order Hemiptera, family Reduviidae and subfamily Triatominae

(Justi and Galvao 2017). The subfamily Triatominae is divided into five tribes, (Alberproseniini,

Bolboderini, Cavernicolini, Rhodniini, and Triatomini), and 18 genera (Justi and Galvao 2017).

Over 140 triatomine species have been described, all of which are considered potential transmitters of T. cruzi (Justi and Galvao 2017).

Triatomines have a wide geographical distribution from the Great Lakes of North America to the province of Chubut in Southern Argentina (Schofield and Galvao 2009). Outside of

America, they are found in Africa, Asia, and Australia, with seven species found exclusively in

Africa and Asia (Gorla, Dujardin et al. 1997, Schofield and Galvao 2009).

Over 140 triatomine species have been described, all of which are considered potential transmitters of T. cruzi (Justi and Galvao 2017). In the present work, four species have been chosen, two from North American countries (Meccus pallidipennis and Triatoma lecticularia) and two from South America (Panstrongylus herreri and Rhodnius prolixus) (Figure 1.2). These species have been selected due to their potential vector capacity of T. cruzi and parasitism in different hosts beside of their different geographical distribution, and adaptation to an urban environment. The description of the characteristics of these species are described below.

Meccus pallidipennis

The triatomine Meccus pallidipennis, formerly known as Triatoma pallidipennis, is one of the most prevalent species in Mexico and accounts for the highest rate of T. cruzi infection (Ibarra-

Cerdena, Sanchez-Cordero et al. 2009, Martinez-Ibarra, Nogueda-Torres et al. 2012). Together

3 with six other species of the Meccus genus, they are responsible for 74% of the T. cruzi transmission (Martinez-Ibarra, Nogueda-Torres et al. 2012).

In general, M. pallidipennis has a relatively short biological cycle (five to six months), which favors the appearance of large populations in a short time (Franzim-Junior, Mendes et al.

2018). In addition, it presents a high rate of eggs and low mortality, factors that increase its incidence and dispersion and consequently its importance in the vector transmission of T. cruzi

(Martinez-Ibarra, Nogueda-Torres et al. 2014).

Triatoma lecticularia

Triatoma lecticularia can be found in the U.S.A. and Mexico and is one of the five most frequently encountered triatomines in Texas, present in domiciles and thus involved in human bites

(Ibarra-Cerdena, Sanchez-Cordero et al. 2009, Wozniak, Lawrence et al. 2015, Curtis-Robles,

Hamer et al. 2018, Grant-Guillen, Nogueda-Torres et al. 2018). An epidemiological survey on wild triatomines in Texas, found a wide geographical distribution of triatomines across the state and an overlap of species. They also verified an association of the triatomines of the species T. lecticularia, T. gerstaeckeri and T. sanguisuga, with human dwellings, and more than half of the specimens found inside or near houses were infected with T. cruzi (Kjos, Snowden et al. 2009).

In addition to the ease of adaptation that culminates in a great dispersion capacity and the possibility of domiciliation, another extremely important characteristic of T. lecticularia, for its effective transmission of T. cruzi, is the defecation time of less than 10 min (average of 6 to 9 min) and consequently, less than the feeding time, which varies approximately from 19 to 24 min

(Martinez-Ibarra, Alejandre-Aguilar et al. 2007).

4 Panstrongylus herreri

The triatomine Panstrongylus herreri also called Pantrongylus lignarius (Marcilla,

Bargues et al. 2002) is found in several countries of South America, including Ecuador, Colombia,

Guyana, Suriname, Venezuela, and Brazil and is the main vector of T. cruzi in Peru (Teixeira,

Monteiro et al. 2001, Patterson, Barbosa et al. 2009).

P. herreri is found in both tropical and subtropical forests, it is predominantly a wild species, occupying palm trees, bird nests and rodent dens, except in Peru, where it is mainly synanthropic (Patterson, Barbosa et al. 2009). Surveillance studies show a considerable number of

P. herreri infected with T. cruzi, giving support for studies on this wild species with a history of domiciliation (Teixeira, Monteiro et al. 2001).

Rhodnius prolixus

The triatomine Rhodnius prolixus has great importance in the vectorial transmission of

ChD, it is the main vector of T. cruzi, the first non-dipteran insect vector to have the genome sequenced and the model organism for the study of triatomine physiology (Mesquita, Vionette-

Amaral et al. 2015, Nunes-da-Fonseca, Berni et al. 2017). It is widely distributed among Central

American countries (Mexico, Guatemala, El Salvador, Costa Rica, Honduras, Nicaragua, and

Panama) and South America (Bolivia, Colombia, Ecuador, Guyana, Suriname, French Guiana,

Venezuela, and Brazil) (Galvao and Justi 2015).

In the Atlantic Forest area, 56% of triatomines collected were infected with T. cruzi.

Triatomines establish colonies in leaves of pteridophytes, animal nests, and palm trunks. Some characteristics of R. prolixus increase its importance in the transmission of the parasite, such as marked anthropophilic, rapid developmental cycle, culminating in high density and intense

5 dispersion, the habit of defecating immediately after feeding and ease into harbor T. cruzi. Among the species of the genus Rhodnius, despite the similarities, the species R. prolixus has the highest feeding efficiency, reaching high intake values, allowing them to reach higher densities

(Sant'Anna, Diotaiuti et al. 2001) .

6 1.3 HEMATOPHAGY AND BIOMOLECULES PRESENT IN SALIVA

Nymphs and adults feed on blood. First, the triatomine probes the host skin with its mouthparts

(Soares, Carvalho-Tavares et al. 2006, Soares, Araujo et al. 2014). Next, it introduces its proboscis into the skin, releasing the saliva in the surrounding tissues and directly into the blood vessels. The injury caused by the feeding process triggers a series of events in the host. Therefore, to successfully complete a meal, these arthropods count on the saliva composition. The bioactive molecules in the saliva include analgesics, anti-hemostatic (vasodilators, anti-platelets, and anti- coagulants), anti-inflammatory, and immunomodulators (Fontaine, Diouf et al. 2011, de Araujo,

Bussacos et al. 2012, Santiago, de Araujo et al. 2020).

Most of the molecules described so far are proteins that antagonize the hemostatic system

(Fontaine, Diouf et al. 2011, de Araujo, Bussacos et al. 2012, Santiago, de Araujo et al.). It includes lipocalins, apyrases, amine-binding proteins, cysteine-rich secretory proteins, Kazal-type, serine proteases, and serine protease inhibitors. One protein that has been extensively studied is the protein nitrophorin (NP) present in the R. prolixus saliva (Ribeiro and Walker 1994, Weichsel,

Andersen et al. 1998, Andersen, Ding et al. 2000, Montfort, Weichsel et al. 2000). NPs are lipocalins that carry nitric oxide (NO). Once in the skin, the differences in pH affects the structure of the NPs, which cause the release of NO. After being released in the host, NO causes vasodilatation. Free NPs can also bind to histamine and prevent pain, swelling, and allergic reactions (Andersen, Gudderra et al. 2005).

The drastic change in environment, from insect saliva to host skin, can directly affect the salivary molecules structure. In the specific case of NPs, the changes did not damage the protein but some sensible ones might have their functions completely impaired. In this context, the presence of extracellular vesicle (EVs) can be the mechanism used by the vector to deliver some

7 of their proteins to the host. The presence of EVs have been shown already in tick saliva but not in triatomine saliva (Hackenberg and Kotsyfakis 2018). Thus, EVs might be important players in the communication between vector-host.

Besides NPs that can prevent some inflammatory effects by sequestering histamine, molecules causing allergies, such as procalins and antigen 5-like proteins, have also been described

(Ribeiro, Andersen et al. 2004, Assumpcao, Francischetti et al. 2008, Kato, Jochim et al. 2010).

Although specific molecules have not been identified, the triatomine saliva is also able to modulate the complement system and some immune cells, like dendritic cells (Barros, Assumpcao et al.

2009, Mendes, Carvalho-Costa et al. 2016).

Regarding lipids, only a few classes have been identified, such as lyso-phosphatidylcholine

(LPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), phosphatidylinositol (PI), and phosphatidic acid (PA) (Golodne, Monteiro et al. 2003). In the feeding context, LPC plays an important role, where it presents anti-hemostatic properties and is able to modulate macrophages (Mesquita, Carneiro et al. 2008, Silva-Neto, Carneiro et al. 2012,

Lima, Carneiro et al. 2018). Currently, metabolomic studies in the triatomine saliva have not yet been performed.

The main role of the salivary molecules is to facilitate the feeding process for the triatomine, but as side-effects they also enable the transmission of T. cruzi (Mesquita, Carneiro et al. 2008, Mendes, Carvalho-Costa et al. 2016, Lima, Carneiro et al. 2018). Its immunomodulatory properties, such as the ability to attract immune cells and inhibit the production of proinflammatory cytokines, increase the association of the parasite and the immune host cells, which results in an increase of parasitemia in the host (Mesquita, Carneiro et al. 2008, Mendes, Carvalho-Costa et al.

2016, Lima, Carneiro et al. 2018). Additionally, the host’s antibody response against the salivary

8 antigens can be exploited as an epidemiological tool for vector exposure and surveillance

(Schwarz, Medrano-Mercado et al. 2010, Dornakova, Salazar-Sanchez et al. 2014).

In summary, although data in the literature showing the presence of proteins mostly by transcriptomic studies and few lipids in the saliva exists, deeper studies by proteomics, lipidomics and metabolomics are still incipient (Faudry, Rocha et al. 2004, Ribeiro, Andersen et al. 2004,

Santos, Ribeiro et al. 2007, Assumpcao, Francischetti et al. 2008, Mesquita, Carneiro et al. 2008,

Kato, Jochim et al. 2010, Bussacos, Nakayasu et al. 2011, Bussacos, Nakayasu et al. 2011, Silva-

Neto, Carneiro et al. 2012, Lima, Carneiro et al. 2018)

9 1.4 SIGNIFICANCE, HYPOTHESIS AND SPECIFIC AIMS

My dissertation project intend to add knowledge about the saliva composition, which can be useful to uncover the mechanisms by which triatomines are able to modulate the host-defense response to facilitate their feeding and most importantly how the saliva can help in T. cruzi transmission. Although the transmission is through the feces, the saliva is still an important attribute because the vectors need a full meal to defecate while still feeding at the host. Thus, the molecules present in saliva are crucial to obtain a good blood flow (Ribeiro and Francischetti 2003, de Araujo, Bussacos et al. 2012, Santiago, de Araujo et al. 2020). Moreover, the saliva can modulate cells at the bite site, where the T. cruzi will get in, and can favor T. cruzi transmission

(Mesquita, Carneiro et al. 2008, Silva-Neto, Carneiro et al. 2012, Mendes, Carvalho-Costa et al.

2016).

Furthermore, as most of the molecules present in the saliva have not yet been described

(mainly, lipids and metabolites), we hope to use this study to identify and characterize proteins, lipids and metabolites. Here, we will focus in the molecules with immunomodulatory effects, which are most likely involved in the transmission of the parasite. This will heighten the awareness of the potential effects of triatomine saliva in the establishment of T. cruzi infection within the mammalian host.

To future researchers, this dissertation will contribute to the creation of a database of bioactive molecules of triatomine saliva that can be useful knowledge for the development of biomarkers of vector exposure and novel drugs, with anti-hemostatic, anti-inflammatory, or immunomodulatory effects (Leitner, Wali et al. 2015). In summary, this study will add more knowledge and new data about the saliva composition and host-parasite interactions.

10 Previous studies have shown that saliva-derived proteins (e.g., lipocalins and nitrophorins) and lipids (e.g., C16:0-LPC) can modulate the host immune system (Ribeiro and Walker 1994,

Weichsel, Andersen et al. 1998, Andersen, Ding et al. 2000, Mesquita, Carneiro et al. 2008). Thus, we hypothesize that the triatomine saliva contains several other proteins, lipids and metabolites that can modulate the mammalian host immune response and the identification of them is a key step for comprehend the ectoparasite-T. cruzi-host interaction.

Our hypothesis will be tested with the following specific aims:

(1) Perform a comprehensive comparative mass spectrometry (MS)-based proteomic, lipidomic and metabolomic analysis of the saliva of the four major triatomine species.

(2) Test the immunoreactivity of the triatomine saliva against ChD human serum pool

(ChHSP) and normal human serum pool (NHSP) from endemic and nonendemic regions.

In the Chapter 1, we have made a brief introduction on the main protagonists of this work, the triatomine species, the T. cruzi and the salivary molecules in the triatomines saliva. The focus of Chapter 2 is to conduct the first in-depth high-resolution comparative proteomic analyses in the saliva of triatomines from North and South America. The immuno-reactivity to ChHSP and

NHSP will be also addressed in Chapter 2. The lipidomic and metabolomic analyses will be approached in Chapter 3. Then finally, Chapter 4 will address conclusions and future directions.

Figure 1.1. Trypanosoma cruzi life cycle.

When feeding in an T. cruzi-infected host, the hematophagous triatomine can also ingest bloodstream trypomastigotes (1), which inside the insect will differentiate into epimastigotes (2), the replicative form of the parasite. The epimastigotes will then transform into the infective metacyclic trypomastigote form (3). In the next blood meal, this form can be eliminated together with the feces near the insect bite injury. The transmission occurs when the host scratches the region, inoculating the bite wound or exposed mucosa with the contaminated feces. The biomolecules present in the saliva, besides helping in the blood feeding process, have also the ability to increase the infection facilitating the trypomastigote to invade host immune cells. Inside these cells, the infective forms will transform into intracellular amastigotes (4), and ultimately into bloodstream trypomastigotes that can be ingested by a vector, and a new cycle will start (5).

Figure 1.2. Triatomine species chosen for this study and their geographical distribution.

Triatomines of four species were used, two from North America countries (Meccus pallidipennis and Triatoma lecticularia) and two from South America (Panstrongylus herreri and Rhodnius prolixus).

13 Chapter 2: In-depth high-resolution proteomic analysis of triatomines saliva from distinct geographical locations reveals substantial differences in their proteome profiles and immunoreactivity*

2.1 INTRODUCTION

Systems biology or omics studies such as proteomics, lipidomics, and metabolomics, have a big impact on the discovery of new salivary molecules. Many proteins have already been found in different triatomine species, mostly by transcriptomic studies (Faudry, Rocha et al. 2004,

Ribeiro, Andersen et al. 2004, Santos, Ribeiro et al. 2007, Assumpcao, Francischetti et al. 2008,

Kato, Jochim et al. 2010, Bussacos, Nakayasu et al. 2011, Bussacos, Nakayasu et al. 2011).

Most of the previous proteomic studies used a more limited and non-high-resolution methodology, which resulted in the description mainly of the highly abundant proteins with functions very closed related with the feeding process (Bussacos, Nakayasu et al. 2011, Costa,

Sousa et al. 2011, Montandon, Barros et al. 2016). A practical application of salivary proteins from vectors is the use of antigenic proteins as new biomarkers of bite exposure and the use of high- resolution proteomic analysis could improve the discovery of such antigenic proteins.

The triatomine saliva is able to interact with several immune cells, such as dendritic cells, macrophages, and B cells (Mesquita, Carneiro et al. 2008, Schwarz, Helling et al. 2009, Schwarz,

Sternberg et al. 2009, Schwarz, Medrano-Mercado et al. 2010, Mendes, Carvalho-Costa et al.

2016). Triatomine saliva proteins stimulate the production of specific antibodies against them. The detection of these antibodies against salivary proteins may be used as a tool for the surveillance of

* Note: This chapter is the basis for the manuscript 19 (see list of publications and manuscripts): Mendes, M.T., et al. In-depth high-resolution proteomic analysis of triatomines saliva from distinct geographical locations reveals substantial differences in their proteome profiles and immunoreactivity. In preparation.

14 bite exposure (Schwarz, Medrano-Mercado et al. 2010, Dornakova, Salazar-Sanchez et al. 2014).

Therefore, the use of these antibodies can be useful for the identification of a population at risk, measurement of the prevalence and intensity of infestations, search or surveillance of unique or multiple species in the same area, detection of re-emerging insect-vector species and as an indicator of autochthone transmission. Knowing the saliva composition can be useful for choosing the best biomarkers. Information distinguishing species-specific proteins vs. shared ones by the different genus can be useful in that context.

In this study, an in-depth high-resolution proteomic analysis was performed, followed by immunoreactivity in ChD human sera pool (ChHSP) and normal human sera pool (NHSP) from endemic and nonendemic countries. Our objective was to conduct a comparative proteomic study between kissing bugs from North and South America and identify possible biomarkers of bite exposure. Here, we make the original discovery of the presence of extracellular vesicles (EVs) in the triatomine saliva.

15 2.2 MATERIALS AND METHODS

Triatomines and saliva collection

Triatomines of four species (P. herreri, M. pallidipennis, T. lecticularia, and R. prolixus), adults of both sexes, and different days of fasting (7 to 21 days) were used. For each species, three biological samples were prepared with a pool of 10 insects each. The insects were provided by the

Parasitology Department’s insectary at Federal University of Triângulo Mineiro (UFTM),

Uberaba-MG, Brazil. Saliva was obtained as described (Mesquita, Carneiro et al. 2008). Briefly, the triatomines were anesthetized on ice, cleaned with deionized water and 70% ethanol, and the salivary glands were extracted according to the species. The triatomine R. prolixus had their heads pulled out with forceps, allowing exposure of the salivary glands and their collection. To collect the glands of the other three species, the side of the abdomen and chest were sectioned and through the aid of a stereoscopic microscope and tweezers, the glands were located and collected. Glands were kept on ice throughout the procedure, and to every three pairs of glands from three insects,

10 µL of sterile saline solution was added. With the aid of sterile needles, the salivary glands were pierced and centrifuged at 11,000 xg for 5 min, at 4oC to allow leakage of saliva. The supernatant was collected and freeze-dried.

Ultra-filtrated saliva (UF-sal) and flow-through saliva (FT-sal)

Ultra-filtrated saliva (UF-sal) was obtained according to Lane et al., 2017, by centrifuging the saliva in Amicon ultra-0.5 centrifugal filters (ref: UFC510024, 100kDa Merk Millipore Ltd.,

Tullagreen, Carrigtwohill, Co. Cork, Ireland) at 14,000 xg for 10 min (Lane, Korbie et al. 2017).

The flow-through was kept and the concentrated sample was recovered by placing the ultrafilter device upside down in a clean microcentrifuge tube and centrifuged at 1,000 xg for 2 min.

16 Nanoparticle Tracking Analysis (NTA)

Nanoparticle tracking analyses (NTA) were performed using NanoSight model LM14C

(NanoSight Technology, Salisbury, United Kingdom), equipped with a green laser and a sCMOS camera (Hamamatsu Photonics K.K., Hamamatsu City, Japan). The software used for capturing and analyzing the data was the NTA 3.2 Dev Build 3.2.16. Three measurements of the same sample were performed in 20-s intervals using the default settings of the instrument. The error bars indicate the standard error of the mean.

Proteomic Analysis

Saliva protein concentration was determined using the bicinchoninic acid (BCA) kit

(Thermo Fisher Scientific). Forty micrograms of protein was resuspended in urea, reduced with 5 mM dithiothreitol (DTT), alkylated with iodoacetamide (IAA), and digested using trypsin, overnight at 37°C, through a filter-aided sample prep (FASP) kit (Expedeon, San Diego, CA), according with manufacture instructions and suggested amounts. Peptides were eluted from the filter with 0.1% formic acid and the sample was then dried in a vacuum centrifuge (CentriVap

Concentrator, Labconco).

The proteomic analysis was performed in the QE-Plus Orbitrap mass spectrometer (QE

Plus-MS; Thermo Fisher Scientific, San Jose, CA), through 1D LC-MS/MS analyses. Tryptic peptides were dissolved in 0.1% formic acid (1 µg/µL) and 1 µL was loaded onto a reversed-phase column (PicoChip, 75 µm ID x 15 µm tip, in-house packed with 10.5 cm of Reprosil -PUR C18 3

µm 120Å; 25 µm x 50 cm fused-silica tail, New Objective) at 300 nL/min rate, for 120-min.

Elution of peptides was carried out in a multi-step gradient (5 to 40% for 95 min; 40 to 95% for 5 min; 95% for 9 min; and 95 to 5% for 11 min) of solvent B [solvent A: 0.1% formic acid, 5%

17 acetonitrile (ACN); solvent B: 0.1% FA, 80% ACN]. MS spectra were collected at a mass resolution of 70,000, in a scan range of mass-to-charge ratio (m/z) of 400 to 1600, and AGC target value of 1E6. The ten most abundant ions were subjected to fragmentation at a mass resolution of

17,500 (ACG target 2E5, NCE 28%, isolation width of 4 m/z).

Database-independent analysis (DBI)

The database-independent (DBI) analyzes were done by the program DiagnoProt, according to the developers’ instructions (Silva, Lima et al. 2017). The software can be downloaded online here (http://patternlabforproteomics.org/diagnoprot/index.html). Raw mass spectra files obtained from the QE Plus-MS (Thermo Fisher Scientific) were used. Default settings were used for the knowledge base creation, except for the Bin Offset set as 0 and the Bin Size set at 0.02.

Database-dependent (DBD) analysis

Raw mass spectra files obtained from QE Plus-MS were analyzed using Proteome

Discoverer 2.1.1.21 (Thermo Fisher Scientific). The database was built by merging 45,589 triatomine proteins downloaded from UniProt (Meccus and Panstrongylus: July 6, 2016; Rhodnius and Triatoma: July 15, 2016), and 11,507 proteins virtually translated from the transcriptome of

P. herreri (Nevoa, Mendes et al. 2018). Scaffold Q+ 4.8.7 (Proteome Software, Portland, OR) was used to validate MS/MS-based peptide and protein identifications. Protein identification was acceptable if the protein was identified by at least 2 peptides with high probability (protein threshold of 99% and peptide threshold of 95%). Heatmap was built using the Scaffold perSPECtives 2.1.0 (Proteome Software). Based on the normalized weighted spectrum count,

18 Venn diagrams were generated by the program FunRich 3 (http://www.funrich.org/). After the identification, proteins with less than 3 normalized weighted spectrum count were filtered out.

BLAST analysis

Triatomine salivary protein sequences were compared to several databases by Basic Local

Alignment Search Tool (BLAST/2.9.0+), using blastx or rpsblast algorithm. These databases were: the non-redundant protein database (NR) of the National Center for Biotechnology Information

(NCBI); the Swiss-Prot database; the “Diptera” salivary sequences from downloaded from NCBI containing the KOG; the COG database: an updated version includes eukaryotes; the Pfam protein families database; and SMART (Bateman, Birney et al. 2000, Schultz, Copley et al. 2000, Tatusov,

Fedorova et al. 2003). The protein sequences were also sent to SignalP server (Nielsen,

Engelbrecht et al. 1997), to the TMHMM server (Sonnhammer, von Heijne et al. 1998) to detect membrane helices; the NetOglyc server to detect possible mucin-type glycosylation (Hansen, Lund et al. 1998), and to the ProP server (Duckert, Brunak et al. 2004) to identify putative furin- processed protein cleavage sites. The protein sequences were also clustered progressively from

25% to 90% similarity over 50% of the length of the larger sequence, thus helping to identify related protein families. To functionally classify the protein sequences, a custom program was written using a vocabulary of ~ 400 words, the e-value of the blast results and a coverage of > 75%,

The classification of “unknown” was given if no match could be found. The final results presented were in many cases manually corrected.

19 Human Blood Sampling and Ethics Statement

Sera used in this study came from six different countries: Mexico, U.S.A, Spain, Bolivia,

Argentina and Brazil, provided from previous studies. ChD human sera pool (ChHSP) and normal human sera pool (NHSP) corresponded to the pool of 10 patients with a positive result or not for

ChD. NHSP were from Mexico, U.S.A. and Spain.

All human samples were collected in accordance with the Good Clinical Practice guidelines and the Declaration of Helsinki, upon approval by the ethical committees of the participating institutions (UTEP; Instituto Nacional de Salud Pública, Tapachula, Mexico;

Fundación CEADES/Universidad Mayor San Simón, Cochabamba, Bolivia; ISGlobal/Hospital

Clínic Barcelona, Barcelona, Spain; Universidad Central de Venezuela, Caracas, Venezuela; and

Universidad Nacional de Salta, Salta, Argentina).

Antibody Levels Testing

Chemiluminescent ELISA (CL-ELISA) was carried out for screening the IgG response to the four species of triatomine saliva, essentially as previously described with modifications

(Schocker, Portillo et al. 2016, Torrico, Gascon et al. 2018). Briefly, 96-well polystyrene microplates (Maxisorp, Nunc, Thermo Scientific Scientific) were coated with triatomine saliva, according to the desired concentration, overnight (16 h), at 4°C. Triatomine saliva was initially immobilized in the microplate at 5,000 ng/well in 200 mM carbonate-bicarbonate buffer, pH 9.6

(CBB), and serially diluted (1:2) to 78.12 ng/well on the microplate wells to a final volume of 50

μL/well. Residual antigen (Ag) was removed by inverting the microplate and tapping it onto absorbent paper towels. Free binding sites of the wells were blocked with 200 μL 1% BSA-PBS

(BSA, Thermo Fisher Scientific) to avoid undesired non-specific binding and microplates were

20 sealed with plastic wrap and incubated for 1 h at 37°C. Plates were then washed three times with

200 μL/ well with PBS-0.05% Tween 20 (PBS-T; Sigma-Aldrich) using an automatic plate washer

(El406 washer, BioTek). ChHSP and NHSP from endemic and nonendemic countries were diluted to 1:200 (in PBS-T + 1% BSA (PBS-TB)), in duplicate, in a final volume of 50 L/well. Plates were incubated for 1 h at 37°C and then washed three times with PBS-T. ChHSP and NHSP were diluted to 1:800 and used in triplicate as positive and negative controls, respectively, against a neoglycoprotein Galα1,3Galβ1,4GlcNAcα-BSA (NGP24b) (Schocker, Portillo et al. 2016), which was used as the reaction positive control at 100 ng/well, to test the protocol functionality and assay reactivity of each microplate. Fifty microliters per well of PBS-TB, with no added serum, was also included to address background nonspecific reactivities. Secondary goat anti-human IgG (H +L) biotinylated antibody (Thermo Scientific Scientific) was prepared in PBS-TB and 50 μL/well, at

1:10,000 dilution, and added to microplates before incubation period for 1 h at 37°C. Plates were washed three times to eliminate unbound antibodies and horseradish peroxidase (HRP)-conjugated streptavidin (Invitrogen) was used (50 μL/well in PBS-TB) at 1:5,000 dilution. Due to light- sensitivity of the reagents, plates were covered with aluminum foil and subsequently incubated for

1 h at 37°C. Plates were washed three times and immunocomplexes were detected with 50 μL/well of a chemiluminescent substrate (SuperSignal ELISA Pico Luminol/Enhancer solution (SSLE) and

SuperSignal ELISA Pico Stable Peroxide (SSP) solution (Thermo Fisher Scientific) (SSLE: SSP:

CBB-B, 1:1:8, v/v/v)) in 0.1% BSA. Relative luminescence units (RLU) were immediately measured using the Cytation 5 microplate reader in a luminescence reader function (BioTek

Instruments).

21 Saliva Protein Electrophoresis and Immunoblotting

Salivary proteins were separated by SDS-PAGE on 4% gradient acrylamide gels under reducing conditions (Laemmli 1970). Each lane of the gel used for Coomassie staining contained

10 μg protein, and the ones used for the western blot contained 30 μg protein of crude saliva.

Proteins were denatured for 5 min, at 95 °C, in loading buffer and resolved at 150 V for 50 min followed by 300 V for 1.5 h. After electrophoresis, Coomassie staining was performed. Standard proteins (Prestained Protein Marker, New England Biolabs) was included in one lane of the gel.

The proteins of a second gel were transferred for western blot analysis onto a nitrocellulose membrane at 200 mA for 1.5 h. Following the transfer, the membrane was incubated with 5% dried skim milk in PBS overnight at 4°C. The membrane was washed five times in PBST and then incubated with appropriate sera diluted 1:800 in PBST with 5% dried skimmed milk for 1 h at room temperature (RT). ChHSP from Mexico and USA were pooled and named North America

Pool. ChHSP from Brazil, Venezuela, Argentina and Bolivia were pooled and called South

America Pool. NHSP from Mexico, U.S.A. and Spain were pooled and used as negative controls.

After repeated washing steps, the membrane was incubated for 1 h at RT with HRP conjugated rabbit anti-human IgG secondary antibodies (Sigma-Aldrich) diluted at 1∶20,000 in PBST with 5% dried skim milk.

Data Analysis

The difference between two independent groups (i.e., normalized weighted spectrum count between UF-sal vs. FT-sal) was determined using the Student’s t-test with a p < 0.05 and correction of Benjamini-Hochberg, performed by Scaffold Q+ 4.8.7 (Proteome Software, Portland, OR).

22 Repository Data

The MS proteomic data have been deposited to the ProteomeXchange Consortium via the

PRIDE (Perez-Riverol, Csordas et al. 2019) partner repository with the dataset identifier

PXD015852 and 10.6019/PXD015852.

23 2.3 RESULTS

General Description of the Proteomic analysis in total saliva

Saliva from four different species of triatomines, two from North America (T. lecticularia, and M. pallidipennis) and two from South America (R. prolixus and P. herreri) was collected as described in Methods and analyzed through MS-based proteomic analysis. A HR-LC-MS/MS, gel- free approach, was used to improve protein coverage. The MS data obtained were subjected to two different analyses, database-independent (DBI) and database-dependent (DBD). The study workflow is summarized in Fig. 2.1. As the names suggest, one of the analysis requires the use of a database search and the other one does not. Normally, the databases are translated from genomic data. Between the four species chosen for this study, only R. prolixus has the complete genome published (Mesquita, Vionette-Amaral et al. 2015). Thus, in order to get a better overview of the data both DBI and DBD analyses were used. It is important to highlight that the same database was used for the four species and built as described in Materials and Methods section.

In the DBI analysis, 1,126,892 spectra were explored, grouped in 294,606 clusters, and a knowledge base (KB) was created. The KB generated revealed 70,800 spectral clusters to be exclusive to R. prolixus, 70,733 to T. lecticularia, 79,402 to P. herreri, and 60,534 to M. pallidipennis. The numbers revealed that 21-27% of the total number of clusters is species-specific

(M. pallidipennis, 21%; R. prolixus and T. lecticularia, 24%; and P. herreri, 27%).

Principal component analysis (PCA) was also generated and allowed for the visualization of how close the species and biological samples were from each other. Each biological replicate, three for each species, was averaged using two technical replicates using a pool of more than 10 insects each. DBI PCA plot showed a clear separation with no overlaps between the four different species of triatomines and showed an effective clustering between the three biological samples (Fig. 2.2A).

24 This indicates a diverse proteomic profile between the different species of triatomines and a consistent data reproducibility. No clustering regarding geographical origin was detected. Through the DBI analyses, T. lecticularia (North America) and P. herreri (South America) clustered closely to each other.

An in-depth high-resolution proteomic analysis followed by a database search allowed the identification of a high number of proteins. To increase the reliability of the protein identification, proteins identified by at least two peptides with high probability (protein threshold of 99% and peptide threshold of 95%) were accepted. Using these criteria, the DBD analysis allowed the identification of 2,589 proteins in total, 1,389 in R. prolixus, 1,821 in T. lecticularia, 2,322 in P. herreri, and 1,731 in M. pallidipennis. Following the identification, these proteins were also filtered based on the normalized weighted spectrum (NWS) count; proteins with three or more

NWS count were selected. As a result of filtering, the protein number narrowed down to 2,444 proteins in total, 894 in R. prolixus, 1,578 in T. lecticularia, 1,821 in P. herreri, and 1,465 in M. pallidipennis (Fig. 2.2F). Only filtered proteins were used in further analyses.

When comparing the proteins identified in the four species by DBD analysis, we observed that 498 proteins are shared by all four species, 197 are R. prolixus-specific, 104 are T. lecticularia- specific, 316 are P. herreri-specific, and 122 are M. pallidipennis-specific (Fig. 2.2F). The number of proteins shared by all four species represents 20% of the total number of identified proteins, while the exclusive proteins correspond to 8%, 4%, 13%, and 4% of the total number of proteins, respectively for R. prolixus, T. lecticularia, P. herreri, and M. pallidipennis (Fig. 2.2F).

To further compare the proteomic data obtained from the DBD analysis, a BLAST analysis was performed. According to this analysis, from the 2,444 filtered proteins, 436 showed the presence of endoplasmic reticulum (ER)-signal peptide or sequence and were classified as secreted

25 proteins, 1,373 were classified as housekeeping proteins and 635 as unknown. The number of proteins separated per class and per species can also be found in Table 2.1.

The highest number of identified proteins were housekeeping, 1,373 total, 523 in R. prolixus,

1,010 in T. lecticularia, 1,121 in P. herreri, and 910 in M. pallidipennis (Table 2.1). PCA distribution of the housekeeping proteins shows some overlap and suggest a closer relationship between the species T. lecticularia, P. herreri, and M. pallidipennis but not for R. prolixus (Fig.

2.2D). The same trend is also observed with the unknown proteins (Fig. 2.2E).

Among the housekeeping proteins, 26% are shared between the four species. In addition,

20% of unknown proteins are also shared (Fig. 2.2H and 2.2I). The functional classification of the housekeeping proteins can be found in Table 2.2.

Among the 436 secreted proteins, 157 belong to R. prolixus, 90 to T. lecticularia, 222 to P. herreri, and 159 to M. pallidipennis (Fig. 2.2G). PCA plot showed a clear separation with no overlaps between the four species and highly reproducibility of the data (Fig. 2.2C). The secreted proteins represented a highly diverse proteomic profile with only 3% of proteins being shared for all four species (Fig. 2.2G). The percentage of exclusive proteins was high compared with the shared proteins, except for T. lecticularia (R. prolixus, 26.3%; P. herreri, 28.6%; M. pallidipennis,

11.7%; and T. lecticularia, 2%) (Fig. 2.2G).

The percentage of shared housekeeping proteins (26%) and unknown proteins (20%) is higher than the shared secreted proteins (3%). The opposite applies to the exclusive proteins. For instance, in P. herreri the percentage of exclusive secreted proteins (28.6%) is higher than housekeeping (9.3%) and unknown (9.7%) proteins (Fig. 2.2G-I). This indicates a much higher number of conserved proteins in the housekeeping and unknown classes.

26 Although the absolute number of housekeeping proteins was the highest, the secreted proteins were the most abundant considering that absolute numbers are not indicative of abundance. To confirm this, the total spectrum count was divided by the number of identified proteins in each class. In R. prolixus, P. herreri, and M. pallidipennis the average spectrum count per protein was higher in secreted proteins than in the other two classes (231.6, 80.6, and 82.3 respectively) (Table 2.2). However, this trend did not apply to T. lecticularia. The low number of

T. lecticularia-specific proteins in the database could have led to the false idea of the housekeeping being more abundant in this species, which we do not believe is the case. Most likely, the secreted proteins are strongly formed by species-specific proteins, that could be absent from our database.

In order to provide a visual comparison of the secreted proteins, a heatmap was generated.

The heatmap graph displayed the main differences between the four species (Fig. 2.3).

Hierarchical clustering was performed based on the NWS count and the proteins with less than three NWS count are represented in gray. The exclusive proteins are highlighted in the dashed rectangles and are mainly lipocalins. It is important to highlight that although they are from the same family, they are different proteins. The lipocalin family is a very diverse group that share conservatively sequences and fold structures (Flower 1996).

The top 10 most abundant proteins are shown in Table 3. In R. prolixus, 10 out of the top 10 proteins were secreted, in T. lecticularia 0 out of 10, in P. herreri 9 out of 10, and in M. pallidipennis 7 out of 10. The well-studied protein nitrophorin (NP) was the most abundant identified in R. prolixus and nine out of the top 10 were nitrophorins. In T. lecticularia, putative vacuolar h+-atpase v1 sector subunit b (A0A0V0G3F6_TRIDM) of 55 kDa was the most abundant protein found. In P. herreri, the most abundant protein was a protein with 23 kDa (PhSigP-57889), which according to our BLAST analysis corresponds to a triabin. In P. herreri, eight out of the top

27 10 proteins were triabins. Pallidipin 2, a platelet-aggregation inhibitor protein (Noeske-Jungblut,

Kratzschmar et al. 1994), was the most abundant protein identified in M. pallidipennis and it is an exclusive protein.

The molecular masses of the identified proteins varied between 7 and 1,290 kDa, with the majority (~70%) of them having low molecular masses (<50 kDa). The largest protein found had

1,290 kDa (T1I3D0_RHOPR) and it is a housekeeping protein, class cytoskeletal, with the best match to Nesprin-2, found in both P. herreri and T. lecticularia. Regarding the lowest molecular mass, six proteins with 7 kDa were identified (T1HVP7_RHOPR, T1I1H6_RHOPR,

T1I826_RHOPR, T1H8M1_RHOPR, Ph-23, Ph-47763). Among those, only one presented signal peptide (T1HVP7_RHOPR) and was only found in R. prolixus, and according to the blast analysis, it is also a triabin.

Secreted proteins

Lipocalins, Triabins, and Nitrophorins (NPs)

Remarkably, 81% of all the secreted proteins were identified as lipocalins, triabins, and

NPs (the percentage was obtained based on the normalized weighted spectrum count). This group usually made by small carrier proteins is very important for feeding and targeting the hemostatic system (Andersen, Gudderra et al. 2005, Ganfornina 2013). The specific percentage of this group within the secreted proteins for each species was 92% for R. prolixus, 71% for P. herreri, 74% for

M. pallidipennis and 30% for T. lecticularia. In R. prolixus, the percentage was the highest, and the percentage correspondent to only NPs reached 57% of the secreted proteins and 52% of the total saliva. This high abundance of NP is responsible for the cherry color of the salivary glands in the Rhodnius species.

28 Besides the identification of five NPs described so far (i.e., NP1, NP2, NP3, NP4, and NP7) in R. prolixus, we also found the presence of NP3 in the proteome of the other three-triatomine species, a novel discovery. NP2 and NP4 were also found in T. lecticularia. Even though nitrophorins were found in non-R. prolixus species the amount was way less compared with R. prolixus. In R. prolixus, different from previews work that showed that the protein NP4 was the most abundant (Montandon, Barros et al. 2016), we found that the most abundant was the NP1. In our results, NP4 was the second most abundant protein in all three biological samples tested of R. prolixus.

One highly abundant triabin identified, was the protein pallidipin, a collagen-induced platelet aggregation inhibitor (Noeske-Jungblut, Kratzschmar et al. 1994). Although the protein pallidipin (Q27042_MECPA) was extremely abundant, it was found exclusively in the species M. pallidipennis. In R. prolixus, two other proteins were identified as pallidipin-like proteins, along with another platelet aggregation inhibitor, known as R. prolixus aggregation inhibitor (RPAI), with molecular mass varying between 19 and 21kDa (Q94732_RHOPR, R4G8L2_RHOPR,

R4G4G7_RHOPR, R4FMZ8_RHOPR), and a biogenic amine-binding protein (ABP)

(Q86PT9_RHOPR) with 24 kDa that also inhibits platelet aggregation and smooth muscle contraction (Andersen, Gudderra et al. 2005). No pallidipin-like proteins were identified in the other two species.

5' nucleotidase (5’NUC ) family (apyrases)

The proteins from this family have been originally described in snake venom and they play a role in the hemostasis process (Iwanaga and Suzuki 1979). Fifteen protein IDs were found to be from the 5' nucleotidase (5’NUC) family, where five were described as apyrases. All four

29 triatomine species presented at least one of them. Their molecular mass varied from 46 to 64 kDa, except the uncharacterized protein, ID T1HHF3_RHOPR, with 21 kDa, which according to the

BLAST analysis is similar to apyrase.

Proteases and protease inhibitors

Proteases and protease inhibitors have been demonstrated in vectors saliva and midgut and are important to block the coagulation cascade (de Araujo, Bussacos et al. 2012). Several trypsin- like serine proteases were identified, mainly in P. herreri and M. pallidipennis with molecular masses varying between 22 and 43 kDa. In R. prolixus, only one trypsin like-protease was identified (PhSigP-61204_FR6_15-316), whereas in T. lecticularia none was found. Other families of proteases were also identified, including papain family cysteine proteases with molecular masses varying between 50 and 63 kDa were detected in P. herreri and M. pallidipennis saliva; aspartyl proteases, with molecular masses from 42 to 46 kDa, mainly in P. herreri and M. pallidipennis, and to a much lesser extent in T. lecticularia (2) and R. prolixus (1). Peptidases were also identified in P. herreri and M. pallidipennis. Regarding protease inhibitors, a putative inter- alpha-trypsin (A0A0V0G5B4_TRIDM) with 81 kDa was identified in P. herreri and M. pallidipennis. Moreover, in M. pallidipennis, another protease inhibitor was identified, the pacifastin serine proteinase inhibitor (A0A170Z969_TRIIF). The protease inhibitor dipetalogastin was identified in all four triatomine species. carboxypeptidase inhibitors were also found in R. prolixus, P. herreri, and M. pallidipennis.

30 Procalin and antigen-5-like proteins (Ag5)

Proteins related to allergic reactions are also a concern in vectors’ saliva, some insect bites can lead to anaphylactic reactions and can be fatal (Pinnas, Lindberg et al. 1986, Paddock,

McKerrow et al. 2001, Klotz, Klotz et al. 2009). Procalin and antigen-5-like proteins (Ag5) are proteins with the allergic activity described in triatomines (de Araujo, Bussacos et al. 2012). Ag5- like proteins were also found in salivary glands of mosquitoes, flies, and tsetse flies (Charlab,

Valenzuela et al. 1999, Valenzuela, Belkaid et al. 2001, Francischetti, Valenzuela et al. 2002).

Procalin-like proteins with a molecular mass of 12 kDa (R4G4Z7_RHOPR) and 22 kDa

(Q7YSZ9_RHOPR) were identified in R. prolixus saliva. Antigen-5-like proteins (Ag5) with molecular mass varying between 26 and 28 kDa were identified in three of the species evaluated.

It was more abundant in R. prolixus and not detected in T. lecticularia.

Phosphatase family

Three acid phosphatases were found in M. pallidipennis, the venom acid phosphatase acph-

1-like protein isoform (A0A170XK82_TRIIF) with 43 kDa, the purple acid phosphatase

(A0A0V0G3H3_TRIDM) with 54 kDa and one with 39 kDa, ID Ph-3384. In P. herreri, a small protein with 14 kDa (PhSigP-58946_FR4_121-239) presented similarities with this family and the prostatic acid phosphatase-like protein (A0A161MGZ0_TRIIF), 29kDa, was also detected. No proteins from the family were detected in R. prolixus or T. lecticularia.

Lysozyme

Lysozymes are proteins able to cause damage in bacterial cell walls causing lysis, as a defense mechanism (Wang 2014). Five proteins were found with molecular masses varying

31 between 14 and 18 kDa. All four-triatomine species presented at least one of them. The ones found in R. prolixus and P. herreri were exclusive proteins.

Esterase/lipase (Lipid metabolism)

Proteins, ranging from 21 to 69 kDa, related to the lipid metabolism were also identified. All four triatomines species presented at least one of them. Carboxylic ester hydrolases were detected in R. prolixus, T. lecticularia, and M. pallidipennis. Putative esterases and lipases were detected in T. lecticularia and M. pallidipennis. The putative palmitoyl protein thioesterase

(A0A0V0G6L7_TRIDM), 35 kDa, was detected in M. pallidipennis. In P. herreri the only one detected was the protein with 21 kDa and ID PhSigP-62662_FR6_46-656.

Miscellaneous proteins

The saliva is composed of not only vasodilators, anti-platelet aggregation, and anticlotting factors but also a cocktail of other molecules such as anesthetics, antibiotics, and odorants

(Fontaine, Diouf et al. 2011, de Araujo, Bussacos et al. 2012). Another family of very small proteins, with molecular masses varying from 14 to 17 kDa, named as the insect pheromone/odorant-binding protein (OBP) was also found in the saliva of all four species. The

OBP family might be important for prey selection (Oliveira, Brito et al. 2017). Moreover, proteins similar to mucins (83-118 kDa) were also detected in the saliva of R. prolixus, M. pallidipennis, and P. herreri. Mucins could be important to the lubrication of the salivary canal (Francischetti,

Lopes et al. 2007).

We also detected two angiotensin-converting enzymes (ACE)-like protein (50 and 72 kDa) in T. lecticularia and M. pallidipennis. ACEs are responsible to convert the inactivate angiotensin

32 I protein to its vasoconstrictor form (Bernstein, Khan et al. 2018). This finding differs from what it is usually found in the saliva of inset-vectors, that is, vasodilators (de Araujo, Bussacos et al.

2012). It is possible, however, that, the ACE-like protein in the saliva has a different function, such as it does in both innate and adaptive responses by modulating macrophage and neutrophil function

(Bernstein, Khan et al. 2018).

Two oxide synthases (132 kDa) were identified: nitric oxide synthase (NOS_RHOPR), which was found in R. prolixus and M. pallidipennis, and the putative NADP-dependent flavoprotein reductase (A0A023FA12_TRIIF), found in R. prolixus, T. lecticularia, and M. pallidipennis. In P. herreri, none of these proteins were detected, whereas both of the oxide synthases were abundant in R. prolixus. Oxide synthases catalyze the production of nitric oxide

(NO). NO plays a role in cellular signaling and in the feeding scenario, it is important for the vasodilation process. In the R. prolixus saliva, the highly abundant protein NPs is the carrier of the

NO (Andersen, Champagne et al. 1997).

In our study, hydrolases were also detected. These proteins could play a role in digestion, because of their ability to break large molecules into smaller ones. The gamma-glutamyl hydrolase

(35-36 kDa) was found in R. prolixus, P. herreri, and M. pallidipennis, which is responsible to remove gamma-glutamyl residues from gamma-glutamate to yield alpha-glutamate (folic acid) and free glutamate (Schneider and Ryan 2006). Moreover, proteins related to lysosomal degradation and antigen processing were also detected, such as the gamma interferon-inducible lysosomal thiol reductase (16-26 kDa) found in R. prolixus, P. herreri, and M. pallidipennis.

A canopy homolog 2 protein, a Toll-like receptor (TLR)-specific co-chaperone, (PhSigP-

62573_FR6_25-216), 22 kDa, was also identified in M. pallidipennis. Proteins with a cystatin-like domain (11-13 kDa), which are able to inhibit peptidase enzymes, were found in R. prolixus. We

33 also identified two toxins, C3 botulinum toxin (Ph-947), 21 kDa, in P. herreri and Zeta toxin (Ph-

62488), 22 kDa, in T. lecticularia, P. herreri, and M. pallidipennis.

A heparin-like protein, anticoagulant (68 kDa), a trialysin (26 kDa), pore-forming protein

(Amino, Martins et al. 2002), a juvenile hormone binding protein (24-27 kDa), a royal jelly protein

(42 kDa) that can be related with some allergic reactions (Rosmilah, Shahnaz et al. 2008), were detected exclusively in P. herreri.

We also found hexamerins (73- 81 kDa) in all four species, which play a role as storage proteins, cuticle formation, transport of hormones and immune defense (Burmester). In all four species, we found transferrins (74 kDa), which bind and transports iron, and apolipophorins-III

(21 kDa), which play a critical role in lipid transport and lipoprotein metabolism (Smith, Owen et al. 1994, Mayle, Le et al. 2012). In addition, we also detected several hypothetical secreted proteins.

Housekeeping

From the housekeeping proteins, the highest percentage is related to protein modification

(Table 2.2). Other highly abundant groups include cytoskeletal proteins, protein synthetic machinery, and signal transduction. In R. prolixus, the most abundant housekeeping protein is the metalloendopeptidase protein (metal binding) detected solely in this species. In T. lecticularia, the most abundant housekeeping was the putative vacuolar h+-atpase protein, already mentioned before. This protein was also found in the other three species. In P. herreri, the most abundant was a protein similar to clavesin, a protein export, also detected in M. pallidipennis. The most abundant in M. pallidipennis was a putative phosphatidylinositol transfer protein also detected in P. herreri.

34 Detoxification proteins have been shown to have a relation with insect’s resistance against insecticides (Sívori, Casabé et al. 1997). We detected several S-transferases proteins belonging to this class in all four species, with R. prolixus having the highest percentage.

Proteomic analysis in ultra-filtrated saliva (UF-sal)

Due to the amount of non-secreted proteins and the presence of EVs in tick saliva

(Hackenberg and Kotsyfakis 2018), we decided to search for EVs in the triatomine saliva as well.

The total saliva was subjected to NanoSight analysis and the presence of EVs was confirmed (Fig.

2.4). The EVs detected exhibited a mean size of 165 nm for R. prolixus, 188 nm for T. lecticularia,

230 nm for P. herreri, and 125 nm for M. pallidipennis (Fig. 2.4A). With the mean size determined, the saliva was filtered in 100-kDa filters. The sample retained in the filter, enriched in EVs, was named ultra-filtrated saliva (UF-sal) and the sample that passed through the filter was named flow- through saliva (FT-sal). Next, the UF-sal, enriched in EVs, and the FT-sal were subjected to proteomic analysis. As previously mentioned in the total saliva, the MS data obtained were subjected to DBI and DBD analysis.

In the UF-sal DBI analysis, 986,530 spectra were explored, grouped in 223,626 clusters, and a knowledge base (KB) was created. The KB generated revealed 66,561 spectral clusters exclusive to R. prolixus, 49,190 to T. lecticularia, 50,007 to P. herreri, and 43,424 to M. pallidipennis. The numbers revealed that 19-30% of the total number of clusters is species-specific (30% to R. prolixus, 22% to T. lecticularia, 22% to P. herreri, and 19% to M. pallidipennis).

The PCA plots showed a clear separation with no overlaps between the four different species of triatomines and an effective clustering between the three biological samples in both samples,

35 UF-sal and FT-sal (Fig. 2.4B,C). The UF-sal also showed a highly similarity between the different species than FT-sal or total saliva.

After the identification of the proteins (DBD analysis), statistical analysis was performed between UF-sal and FT-sal. Proteins with p<0.05 were further analyzed and the results are represented in Fig. 2.4D-G. In R. prolixus, 97 proteins presented higher and 35 lower NWS count in UF-sal than FT-sal. In T. lecticularia, 171 were higher and nine lower; in P. herreri, 327 were higher and 30 lower, and in M. pallidipennis 62 were higher and 19 lower.

Among the proteins highly abundant in UF-sal, independent the species analyzed, we can highlight, heat-shock proteins, actins (cytoskeletal proteins), and ATP-binding proteins.

Significantly abundant proteins in the FT-sal correspond to the highly abundant secreted proteins in the total saliva, such as the NPs in R. prolixus, triabins in P. herreri and Pallidipin in M. pallidipennis. The only exception is for the T. lecticularia, and again we believe this is due to the lack of species-specific proteins in the database.

Antibody responses against total saliva proteins

To test the saliva’s ability to elicit an immune response in the host, screening of total IgG was carried out using ChHSP and NHSP from endemic and nonendemic countries. A dose- dependent reactivity was observed with ChHSP and a differential immunoreactivity was detected between the ChHSP and NHSP (Figs. 2.5 and 2.6A). The ChD serum pool from Mexico exhibited a slightly stronger reactivity with the species T. lecticularia and M. pallidipennis, both found in

North America. ChHSP from the U.S.A. also exhibited a stronger reactivity with the species T. lecticularia and M. pallidipennis, and surprisingly with R. prolixus saliva, a South America species. The species P. herreri also showed a very high result, with both countries not only against

36 ChHSP but also NHSP, which can be indicative of non-specific immune response (Fig. 2.5). The serum pools from South American endemic areas reacted with the saliva of all the four triatomine species, and more strongly with the saliva from P. herreri. Among all countries tested, the ChD serum pool from Spain showed the highest immune response, mainly to P. herreri and less to R. prolixus saliva.

The assay results expressed as the ChHSP/NHSP ratio (positive-to-negative ratio) are represented in Fig. 2.6A. As expected, saliva from T. lecticularia and M. pallidipennis (North

American species) exhibited the highest ratio with serum pools from Mexico and the U.S.A. The

ChD serum pool from the U.S.A. also presented a high ratio with R. prolixus saliva, a South

American species (Fig. 2.6A). As to South American saliva samples, the positive and negative serum pools from Brazil showed the highest ratios with R. prolixus saliva, whereas that from

Argentina, the lowest. T. lecticularia presented the highest ChHSP/NHSP ratio with serum pools from Brazil and Bolivia. Moreover, R. prolixus saliva showed the highest ratio with serum pools from Venezuela, whereas in P. herreri saliva showed a higher ratio with serum pools from

Argentina. Finally, serum pools Spain showed the highest ratio to R. prolixus saliva and the lowest to M. pallidipennis saliva, which also exhibited the lowest ratios with serum pools from Bolivia,

Venezuela, and Argentina (Fig. 2.6A).

Immunogenic proteins in total saliva - Immunoblot

SDS-PAGE of saliva of the four triatomine species revealed a complex protein profile with most of the proteins with relatively low relative molecular masses (Fig. 2.6B). While some bands were shared between the species, there were also variations in the intensity of bands and species- specific bands.

37 Serum pools from ChD from North America, South America, and Europe were used to detect the immunogenic salivary proteins. While the SDS-PAGE demonstrated a complex mixture of proteins, the immunoblot analysis indicates that only a subset of proteins was immunogenic (Fig.

2.6C). Total IgG measured against salivary antigens were mainly detected against proteins between 15 and 25 kDa. The North American ChHSP exhibited antibodies against salivary proteins from the four species, being particularly strongly reactive against R. prolixus, T. lecticularia and M. pallidipennis saliva, and to a lesser extent to P. herreri saliva. The South

American ChHSP showed antibodies against three species, except M. pallidipennis. The European

ChHSP showed antibodies against saliva from three species, but not to T. lecticularia saliva. Serum pools from South America and Europe exhibited IgG antibodies against salivary proteins with higher relative molecular mass (>50 kDa) than the other species and more intense against the South

American ChHSP.

Figure 2.1. Schematic representation of the methodology used.

39 Salivary glands were extracted from four different species of triatomines and the saliva was obtained after centrifugation and elimination of the cell debris. Half of the samples was subjected to ultrafiltration to obtain the ultra-filtrated saliva (UF-sal) enriched with extracellular vesicles

(EVs). The proteins were digested in filter-aided sample prep (FASP) and 1D LC-MS/MS raw files were submitted to database-independent, and database-dependent analyses.

Figure 2.2. Proteomic analysis of the total saliva from the four triatomine species.

Principal component analysis (PCA) from (A) total saliva by DBI-analysis; (B) total saliva, by

DBD-analysis; (C) secreted proteins; (D) housekeeping proteins; and (E) unknown proteins. The

Venn diagrams were generated after DBD analysis and with proteins with three or more NWS count and correspond to the (F) total saliva, (G) secreted proteins, (H) housekeeping, and (I) unknown. DBI, database independent; DBD, database dependent.

Figure 2.3. Heatmap representation of secreted proteins.

Heatmap was generated after DBD analysis by the Scaffold perSPECtives software. Hierarchical clustering was performed based on the NWS count and corresponds to 436 proteins with a signal peptide. Proteins less than three NWS count are represented in gray. The exclusive proteins from each species are highlighted in the dashed square.

Figure 2.4. UF-sal and FT-sal analysis from the four different triatomine species.

(A) Size distribution of EVs released by the triatomine salivary glands. The nanoparticle tracking analysis was determined by NanoSight. (B) PCA from UF-sal generated by DBI analysis. (C) PCA from FT-sal generated by DBI analysis. (D-G) The Venn diagrams correspond to the relative quantitative profile (*p<0.05, Student’s t-test, with Benjamini-Hochberg correction). (D) R. prolixus. (E) T. lecticularia. (F) P. herreri. (G) M. pallidipennis. μ = Mean; σ = standard deviation;

UF-sal = ultra-filtrated saliva; FT-sal = flow-through saliva.

Figure 2.5. Sera from Chagas human sera pool (ChHSP) patients from different countries presents different immune response against salivary antigens from the different triatomines.

Reactivity of ChHSP and NHSP from endemic and non-endemic regions to different triatomine saliva. Each triatomine saliva was tested with several ChHSPs and NHSPs in duplicate. RLU, relative luminescence units.

Figure 2.6. Immunoreactivity of ChD human serum pools against salivary antigens from different triatomines.

(A) Ratio of reactivity of ChHSP with NHSP from endemic and non-endemic regions to different triatomine saliva. (B) SDS-PAGE. (C) Immunoblot (North America countries: Mexico and U.S.A.

South America countries: Brazil, Bolivia, Venezuela, Argentina. Europe: Spain). M, marker; Rp,

R. prolixus; Ph, P. herreri, Mp, M. pallidipennis; Tl, T. lecticularia.

Table 2.1. Number of protein found in the total triatomine saliva.

Average of Number of Spectrum spectrum Species Class proteins a count b count b /protein Secreted 157 36355 231.6 Housekeeping 523 10410 19.9 R. prolixus Unknown 214 4265 19.9 Total 894 51030 Secreted 90 2073 23.0 Housekeeping 1010 34792 34.4 T. lecticularia Unknown 478 13431 28.1 Total 1578 50296 Secreted 225 18131 80.6 Housekeeping 1121 23926 21.3 P. herreri Unknown 476 9229 19.4 Total 1822 51286 Secreted 160 13170 82.3 Housekeeping 910 28418 31.2 M. pallidipennis Unknown 395 9258 23.4 Total 1465 50846

a Number of proteins after filtering ( ≥ 3 normalized weighted spectrum count).

b Normalized total weighted spectrum count.

Table 2.2. Percentage of functional classification of the housekeeping proteins.

Percentage of spectrum count Types of proteins R. T. P. M. prolixus lecticularia herreri pallidipennis Protein modification 27.7 25.8 24.5 31.9 Cytoskeletal proteins 11.5 15.8 11.8 11.8 Protein synthesis machinery 10.8 14.3 8.6 6.8 Signal transduction 11.1 9.0 10.6 9.5 Metabolism, carbohydrate 9.5 8.8 10.0 11.0 Oxidant metabolism/Detoxification 8.3 6.6 6.0 5.1 Transporters and channels 6.9 5.4 5.2 4.8 Metabolism, lipid 1.4 2.7 5.4 3.6 Storage 5.8 2.5 2.6 2.0 Protein export 0.6 1.7 5.0 4.4 Proteasome machinery 1.2 2.2 2.2 2.9 Metabolism, amino acid 1.3 1.5 2.9 2.6 Extracellular matrix 0.8 0.2 1.6 1.5 Transcription machinery 0.7 1.3 0.9 0.6 Metabolism, nucleotide 0.6 0.4 0.5 0.3 Metabolism, Intermediary 0.9 0.2 0.4 0.1 Immunity 0.2 0.3 0.5 0.5 Nuclear regulation 0.2 0.7 0.2 0.1 Transposable element 0.0 0.2 0.8 0.1 Energy metabolism 0.4 0.1 0.2 0.1 Transcription factor 0.3 0.3 0.1 0.1 Nuclear export 0.1 0.0 0.1 0.1

47 Table 2.3. Major proteins (top 10) found in each species of triatomine.

Normalized weighted spectrum count Top 10 Proteins IDs MW Secreted R.p * T.l * P.h * M.p * Nitrophorin-1 OS=Rhodnius prolixus PE=1 SV=1 NP1_RHOPR 23 kDa Yes 2799.10 8.28 0.57 0.39 Nitrophorin 4A OS=Rhodnius prolixus PE=2 Q7YT15_RHOPR 23 kDa Yes 2189.63 3.68 0.57 0.39 SV=1 Nitrophorin-4 OS=Rhodnius prolixus PE=1 SV=1 NP4_RHOPR 22 kDa Yes 2053.24 3.68 0.57 0.39 Putative nitrophorin OS=Rhodnius prolixus PE=2 R4G8M6_RHOPR 23 kDa Yes 2030.93 6.44 0.57 0.39 SV=1 Nitrophorin-2 OS=Rhodnius prolixus PE=1 SV=1 NP2_RHOPR 22 kDa Yes 1678.01 8.28 1.15 0.00 R. prolixus Nitrophorin-3 OS=Rhodnius prolixus PE=2 SV=1 NP3_RHOPR 22 kDa Yes 1356.67 104.89 20.62 4.72 Putative triabin length (Fragment) OS=Rhodnius A0A0P4VJD8_9HEMI 17 kDa Yes 1308.54 34.66 1.15 0.00 neglectus PE=2 SV=1 Putative nitrophorin 1-like OS=Rhodnius prolixus R4G8M9_RHOPR 24 kDa Yes 1304.62 1.66 0.00 0.00 PE=2 SV=1 Nitrophorin-3 OS=Rhodnius prolixus PE=2 SV=1 O77000_RHOPR 22 kDa Yes 1136.24 104.89 20.62 4.72 Putative nitrophorin 1a OS=Rhodnius prolixus R4FPW7_RHOPR 24 kDa Yes 1038.62 0.74 0.00 0.00 PE=2 SV=1 Putative vacuolar h+-atpase v1 sector subunit b A0A0V0G3F6_TRIDM 55 kDa No 84.64 454.54 174.15 284.67 (Fragment) OS=Triatoma dimidiata PE=3 SV=1 Elongation factor 1-alpha OS=Triatoma infestans A0A023FBG1_TRIIF 50 kDa No 87.89 427.85 162.98 256.36 PE=2 SV=1 Elongation factor 1-alpha OS=Panstrongylus A0A069DZ22_9HEMI 51 kDa No 88.82 368.97 145.22 221.76 megistus PE=2 SV=1 Actin (Fragment) OS=Triatoma matogrossensis E2J7J6_9HEMI 30 kDa No 126.44 358.48 144.07 347.71 PE=2 SV=1 Extracted CDS [Panstrongylus herreri] Ph-58384 69 kDa No 6.77 356.45 128.09 278.34 T. Group of Putative tubulin alpha-1 chain R4FNL0_RHOPR (+1) 50 kDa No 93.16 329.71 128.42 210.49 lecticularia OS=Rhodnius prolixus PE=2 SV=1+1 Putative fatty acid-binding protein fabp A0A023F8M4_TRIIF 15 kDa No 10.85 318.67 17.95 33.81 OS=Triatoma infestans PE=2 SV=1 Putative ca2+-binding actin-bundling protein A0A0V0G435_TRIDM 278 kDa No 29.61 295.97 124.60 51.38 OS=Triatoma dimidiata PE=4 SV=1 Protein disulfide-isomerase (Fragment) A0A161MGV7_TRIIF 47 kDa No 5.12 284.93 124.12 181.39 OS=Triatoma infestans PE=4 SV=1 Putative creatine kinase OS=Triatoma dimidiata A0A0V0G573_TRIDM 40 kDa No 36.33 281.56 57.52 85.77 PE=3 SV=1 SigPeptide sequence [Pantrongylus herreri] PhSigP-57889 23 kDa Yes 0.00 0.00 2646.96 0.00 P. herreri SigPeptide sequence [Pantrongylus herreri] PhSigP-61662_FR5_1-203 22 kDa Yes 0.00 0.00 1526.71 699.88 Extracted CDS [Panstrongylus herreri] Ph-59317 20 kDa Yes 0.00 0.00 1113.86 0.00

48 SigPeptide sequence [Pantrongylus herreri] PhSigP-59114_FR6_1-203 22 kDa Yes 0.00 0.00 1042.34 56.62 SigPeptide sequence [Pantrongylus herreri] PhSigP-57453_FR4_1-196 21 kDa Yes 0.00 0.00 814.24 14.15 Extracted CDS [Panstrongylus herreri] Ph-61113 37 kDa No 0.00 0.00 523.70 129.75 SigPeptide sequence [Pantrongylus herreri] PhSigP-45587 22 kDa Yes 0.00 0.00 398.43 0.00 SigPeptide sequence [Pantrongylus herreri] PhSigP-61204_FR6_15-316 33 kDa Yes 14.42 0.00 395.86 0.00 SigPeptide sequence [Pantrongylus herreri] PhSigP-54422_FR3_1-188 21 kDa Yes 0.00 0.00 376.86 0.79 SigPeptide sequence [Pantrongylus herreri] PhSigP-661 22 kDa Yes 0.00 0.00 359.19 183.23 Pallidipin 2 OS=Meccus pallidipennis PE=2 tr|Q27042|Q27042_MECPA 20 kDa Yes 0.00 0.00 0.00 2381.16 SV=1 Uncharacterized protein OS=Triatoma dimidiata A0A0V0G2V8_TRIDM 23 kDa Yes 0.00 0.00 0.29 1193.73 PE=4 SV=1 Uncharacterized protein OS=Triatoma dimidiata D1MWB7_TRIDM 22 kDa Yes 0.00 0.00 0.00 938.15 PE=2 SV=1 Putative triabin OS=Rhodnius neglectus PE=2 A0A0P4VT36_9HEMI 20 kDa Yes 0.00 1.84 0.00 798.96 SV=1 SigPeptide sequence [Pantrongylus herreri] PhSigP-61662_FR5_1-203 22 kDa Yes 0.00 0.00 1526.71 699.88 M. Putative phosphatidylinositol transfer protein A0A069DRX4_9HEMI 37 kDa No 0.00 0.00 113.52 489.92 pallidipennis sec14 (Fragment) OS=Panstrongylus megistus PE=2 SV=1 Uncharacterized protein OS=Triatoma dimidiata D1MWD5_TRIDM 22 kDa Yes 0.00 0.00 0.00 459.25 PE=2 SV=1 Actin (Fragment) OS=Triatoma matogrossensis E2J7J6_9HEMI 30 kDa No 126.44 358.48 144.07 347.71 PE=2 SV=1 Extracted CDS [Panstrongylus herreri] Ph-4439 15 kDa No 17.83 217.45 119.64 346.79 Putative triabin lipocalin (Fragment) A0A0V0G2K7_TRIDM 17 kDa Yes 0.00 0.00 0.00 317.70 OS=Triatoma dimidiata PE=4 SV=1 * The numbers represent the normalized weighted spectrum count.

49 2.4 DISCUSSION

This is the first in-depth high-resolution comparative proteomic analysis of the saliva of triatomines from North and South American species. During evolution, hematophagous vectors feed on different hosts and, therefore, are challenged by various host immune systems and subjected to different evolutionary pressures. These dynamic vector-host interactions might have induced each species to produce and secrete distinct bioactive salivary molecules. To get an insight into the antigenic salivary proteins, the immunoreactivity of ChHSP and NHSP from endemic and non-endemic regions to the saliva of triatomines from four different species was evaluated. We also investigated the presence of EVs in the saliva of these triatomine species.

One of the challenges when working with proteomics is to build a representative database.

In the case of triatomines, only the species R. prolixus has the complete genome, so to better analyze the data, a database-independent (DBI) analysis was also included. With the DBI results, we could see a clear separation with no overlaps between the four different species of triatomines and an effective clustering between the three biological samples, indicating a diverse proteomic profile between the different species of triatomines and highly reproducible data.

No clustering regarding geographical origin was detected. Moreover, through the DBI analyses, T. lecticularia (North America) and P. herreri (South America) clustered closely to each other. It was evident that R. prolixus saliva clusters separated from the other three (both DBI and

DBD). The subfamily Triatominae is divided into five tribes; the two main tribes are investigated here. R. prolixus belongs to the tribe Rhodniini and the species T. lecticularia, P. herreri, and M. pallidipennis to the tribe Triatomini (Justi and Galvao 2017). Thus, this correlates with our PCA data where the proteins from T. lecticularia, P. herreri, and M. pallidipennis are closer together than the ones from R. prolixus, which belongs to a different tribe (Fig. 2D and E).

50 For the DBD analyzes, the database used was built by merging proteins from the R. prolixus genome, P. herreri transcriptome and all triatomine proteins from UniProt database. After the identification of the proteins, they were classified as secreted, housekeeping or unknown. In absolute numbers, the housekeeping proteins seemed to be more abundant. However, after getting the average of the spectrum count per protein, was evident that the secreted proteins were the most abundant. Some discrepancies of results were observed with the species T. lecticularia. The lack of species-specific proteins in the database, mainly T. lecticularia-specific can justify this finding.

When comparing the percentages of exclusive clusters obtained from DBI and exclusive proteins from DBD, we observed that the species-specific number went down from more than 20% (DBI) to less than 13% (DBD), since the DBI is free of any biases, the percentage is higher and may reflect what is indeed real.

When looking at the percentage of shared proteins, we observed a higher percentage in housekeeping (26%) and unknown (20%) than secreted proteins (3%). This indicates a higher number of conserved proteins in the housekeeping and unknown classes instead of secreted proteins and evidence for the evolution pressure on secreted proteins.

The use of FASP coupled with high-sensitivity MS has yielded the most comprehensive proteomic analysis of triatomine salivary proteins to date. For instance, Bussacos et al. (2011) identified 159 proteins in P. megistus saliva; Costa et al. (2011) identified 129 in R. brethesi and

135 in R. robustus; Montandon et al. (2016) identified 221 proteins (69 were from R. prolixus,

100 from T. lecticularia, and 52 from P. herreri), and Hernandez-Vargas identified 78 in M. pallidipennis (Bussacos, Nakayasu et al. 2011, Costa, Sousa et al. 2011, Montandon, Barros et al.

2016, Hernandez-Vargas, Gil et al. 2017). All these previous studies showed a much lower low number of identified proteins than that found in this current study.

51 In our study, such as in previous ones, the most abundant proteins in triatomine saliva belong to the lipocalin group (Assumpcao, Francischetti et al. 2008, Assumpcao, Eaton et al. 2012,

Montandon, Barros et al. 2016, Santiago, de Araujo et al. 2018). This class of proteins is highly diverse and typically composed of small carrier proteins with similar structures. It is related to a variety of different functions, such as transport of small molecules, modulation of the immune response, and clearance of endogenous and exogenous compounds. In the Rhodnius genus, the most abundant lipocalins are nitrophorins, although characteristic of this genus was previously reported in the transcriptome of Triatoma species (Santos, Ribeiro et al. 2007, Santiago, de Araujo et al. 2018) and here for the first time in the proteome of T. lecticularia, M. pallidipennis, and P. herreri.

Among the housekeeping proteins, the largest sets were associated with protein modification, synthesis machinery, cytoskeletal, and signal transduction, which is consistent with salivary glands, an organ specialized in secreting molecules (Santos, Ribeiro et al. 2007, Santiago, de Araujo et al. 2018). Another important set of housekeeping proteins for insets is the oxidant metabolism/detoxification, responsible for insecticide resistance. Proteins such as the S- transferase proteins, belonging to this set of housekeeping and shared by the four species could be used as a target in insecticide resistance studies. S-Transferase proteins have been also identified in R. brethesi and P. megistus (Bussacos, Nakayasu et al. 2011, Bussacos, Nakayasu et al. 2011).

The transition in the environment from insect to host can be dramatic and can directly affect the salivary molecules. For instance, once in the skin, the difference in pH affects the structure of the nitrophorins, which cause the release of NO and the space left is used to sequester histamine.

Some proteins can have their functions completely impaired by these changes, so the use of EVs as a way to carry these proteins to their targets can be driving the evolutionary pressure. Thus, EVs

52 are important players in the communication between vector-host cells and have been the focus for some biomarkers research too (Wu, Wang et al. 2018).

Here, we describe for the first time the presence of EVs in the triatomine saliva. We obtained two salivary fractions, UF-sal and FT-sal. The UF-sal corresponds to the EV-enriched fraction and the FT-sal corresponds to the proteins that went through the filter, the secreted proteins. The statistical analysis performed between UF-sal and FT-sal confirmed our findings.

The UF-sal fraction showed enrichment in proteins related to the biogenesis of EVs, such as the heat shock proteins, actins (cytoskeletal proteins), and ATP binding proteins. Moreover, the FT- sal showed to be significantly abundant in secreted proteins.

Salivary molecules not just from triatomines, but also from other hematophagous arthropods, can stimulate their hosts to produce antibodies, which can be used as epidemiological and surveillance tools (Schwartz, Ford et al. 1991, Schwartz, Nadelman et al. 1993, Hostomska,

Rohousova et al. 2008, Schwarz, Juarez et al. 2011, Dornakova, Salazar-Sanchez et al. 2014).

Therefore, salivary molecules behave as biological markers of exposure to vectors disease. The immune response against the salivary antigens can be affected by different factors, such as duration of exposure and frequency (Schwarz, Helling et al. 2009, Schwarz, Sternberg et al. 2009, Schwarz,

Medrano-Mercado et al. 2010). The higher the exposure, the more robust the antibody response will be (Schwarz, Sternberg et al. 2009). In chickens, IgG antibodies were detected as early as two days after the first bug bites and could be detectable up to 5 months after triatomine exposure

(Schwarz, Sternberg et al. 2009). The IgG response varies with the host and with the triatomine species, which can present stage- and strain-dependent variation (Schwarz, Sternberg et al. 2009,

Dornakova, Salazar-Sanchez et al. 2014).

53 In our study, information about the duration of exposure, frequency, length of time after the bite samples were obtained could not be determined, since the sera used in this study are from chronic ChD patients from endemic and nonendemic regions. However, it is expected that nonendemic countries present lower IgG antibody levels, as we observed here with the results from the serum pools from the U.S.A. The same would be expected with the serum pools from patients from Europe; however, that was not observed. In this last scenario, the migration factor cannot be ruled out.

An ideal biomarker would be able to detect an antibody production regardless of the stage, strain and species of triatomine and would not present cross-reactivity to other hematophagous vectors. Two proteins of 14 and 21 kDa, identified in the sera of chicken challenged with Triatoma infestans, have been considered as a potential biomarkers of triatomine exposure (Schwarz,

Helling et al. 2009, Schwarz, Sternberg et al. 2009). In cross-reactivity experiments, they showed lack of reactivity to bed bugs, mosquito, sandfly or tick saliva and were able to be recognized by sera from chickens exposed to four other triatomine species, Triatoma brasiliensis, Triatoma sordida, R. prolixus, and Panstrongylus megistus (Schwarz, Helling et al. 2009, Schwarz,

Sternberg et al. 2009).

In our results, we observed that sera from North America reacted with R. prolixus saliva, a species not present in that region which correlates with the previous statement, proving that the salivary antigens able to elicit IgG production could be shared by different triatomine species.

Despite that, the North American countries showed a higher antibody production against T. lecticularia and M. pallidipennis, which are North American species. Among the South American countries, the lowest immune response was against M. pallidipennis, a North American species,

54 also showing some geographical correlation. The immune response against the other three species varies by country.

In conclusion, this study showed how similar the different species of triatomine are, and that R. prolixus is indeed the most diverse species of the four. Furthermore, we also revealed the presence of EVs in the triatomine saliva for the first time and demonstrated the potential of triatomine salivary antigens for the detection of exposure to triatomine bites.

55 Chapter 3: Triatomine saliva lipidomic and metabolomics: identification of non-protein

compounds with possible immune effect in the mammalian host *

3.1 INTRODUCTION

Most of the studies describing the saliva composition focus on the proteins, thus far, no global lipidomic or metabolomic analysis of the triatomine saliva by in-depth high-resolution techniques has been done (Faudry, Rocha et al. 2004, Ribeiro, Andersen et al. 2004, Santos,

Ribeiro et al. 2007, Assumpcao, Francischetti et al. 2008, Kato, Jochim et al. 2010, Bussacos,

Nakayasu et al. 2011, Bussacos, Nakayasu et al. 2011).

Few lipids have been reported by thin-layer chromatography (TLC) plates, which are restricted to only the lipid class identification. Lyso-phosphatidylcholine (LPC) has been described in the triatomine saliva of Rhodnius prolixus and Triatoma infestans (Golodne, Monteiro et al.

2003, Chagas-Lima, Pereira et al. 2019). LPC has anti-hemostatic properties which can be fundamental to the feeding process (Golodne, Monteiro et al. 2003). The salivary LPC also induces cell chemotaxis, immunosuppression of NO production, and increases the rate of association of T. cruzi with macrophages which ultimately increases parasitemia (Mesquita, Carneiro et al. 2008,

Silva-Neto, Carneiro et al. 2012).

Despite the fact some lipid classes have already been described in the triatomine saliva, a detailed structural information has been lacking. Lipids are a very diverse group, presenting a diverse range of structures, with differences in chain length and double bonds, which ultimately

* Note: This chapter is the basis for the manuscript 18 (see list of publications and manuscripts): Mendes, M.T., et al. Triatomine saliva lipidomic and metabolomics: identification of non-protein compounds with possible immune effect in the mammalian host. In preparation.

56 can reflect in their functions (Burdge and Calder 2015). No metabolomic analyses have been done in the triatomine saliva so far. The metabolome corresponds to small molecules which are intermediate or end product of metabolism (Alseekh and Fernie 2018). Metabolites have several functions, which can be directly related to the feeding process, such as, signaling, cofactor to an enzyme, odorants, and pheromones.

In summary, in this study, an in-depth high-resolution lipidomic and metabolomics analysis was performed. We aimed to conduct the first comparative lipidomic and metabolomics study in four triatomine species, two from North America (Triatoma. lecticularia and Meccus pallidipennis) and two from South America (R. prolixus and Panstrongylus herreri).

57 3.2 MATERIALS AND METHODS

Triatomines and saliva collection

Three biological samples were prepared with a pool of 10 adults insects of both sexes, and different days of fasting (7 to 21 days). The four species used (P. herreri, M. pallidipennis, T. lecticularia, and R. prolixus) were provided by the Parasitology Department’s insectary in Federal

University of Triângulo Mineiro (UFTM), Uberaba, MG, Brazil. Saliva was obtained as described

(Mesquita, Carneiro et al. 2008). First, the insects were anesthetized on ice, cleaned with deionized water and 70% ethanol. The collection of the salivary glands in R. prolixus was done after its exposition through the extraction of the insect head. In the other three species, the side of the insects were sectioned and through the aid of a stereoscopic microscope and tweezers, the glands were located and collected. Glands were kept on ice throughout the procedure, and to every three pairs of glands (=three insects) 10 µL sterile saline solution was added. With the aid of sterile needles, the salivary glands were pierced and centrifuged at 11,000 xg for 5 min, at 4oC to allow leakage of saliva. The supernatant was collected and freeze-dried.

Extraction of lipids and metabolites

Salivary lipids and metabolites were extracted by Folch's partition (Folch, Lees et al. 1957, Bligh and Dyer 1959). First, the samples were spiked with the internal standard C10:0-LPC (Avanti Polar

Lipids, Cat# 855375C) and resuspended in water and 5 volumes of cold (-20°C) chloroform- methanol (2:1, v/v) solution. Then, samples were incubated for 5 min on ice, subjected to vortex mixing for 1 min, and centrifuged at 13,400 xg for 10 min, at 4°C, to obtain a two-phase system: lower (organic) and upper (aqueous), as previously described (Folch, Lees et al. 1957). Both

58 phases were dried under nitrogen N2 steam and stored at −20°C until use. The summary of the extraction is represented in Figure 3.1.

Lipidomic and metabolomic analyses

Both aqueous (upper) and organic (lower) phases were analyzed by QE-Plus Orbitrap mass spectrometer (QE Plus-MS) (Thermo Fisher Scientific, San Jose, CA), through 1D LC-MS/MS.

Aqueous phases were injected using a C8 column (Kinetex 1.7 µm EVO C8 100Å, LC Column 50 x 2.1 mm, Phenomenex) and separated with a 7.5-min gradient (mobile phase A: high-grade water with 0.1% (v/v) formic acid; mobile phase B: methanol with 0.1% (v/v) formic acid). Organic phases were reconstituted in the mobile phase A (acetonitrile/water (40:60, v/v) containing 10 mM ammonium acetate) with 10% of mobile B (acetonitrile/isopropanol (10:90, v/v) containing 10 mM ammonium acetate) (Nakayasu, Nicora et al. 2016), and injected using a C18 column (Kinetex

2.6 µm EVO C18 100Å, LC Column 150 x 2.1mm, Phenomenex). Eluting molecules were analyzed in both positive- and negative-ion modes.

Lipidomic analysis

The lower phase (organic phase) raw data were analyzed using MS-Dial (version 3.18).

MS-Dial is freely available on the RIKEN PRIME website (http://prime.psc.riken.jp/). The following parameters were used: retention time begin, 0 min; retention time end, 100 min; mass range begin, 0 Da; mass range end, 5000 Da; accurate mass tolerance (MS1), 0.01 Da; MS2 tolerance, 0.025 Da; maximum charge number, 2; smoothing method, linear weighted moving average; smoothing level, 3; minimum peak width, 5 scan; minimum peak height, 1000; mass slice width, 0.1 Da; sigma window value, 0.5; MS2Dec amplitude cut-off, 0; exclude after precursor,

59 true; keep isotope until, 0.5 Da; keep original precursor isotopes, false; exclude after precursor, true; retention time tolerance for identification, 4 min; MS1 for identification, 0.01 Da; accurate mass tolerance (MS2) for identification, 0.05 Da; identification score cut-off, 70%; using retention time for scoring, true; relative abundance cut off, 0; top candidate report, true; retention time tolerance for alignment, 0.05 min; MS1 tolerance for alignment, 0.015 Da; peak count filter, 0; remove feature based on peak height fold-change, true; sample max/blank average, 5; keep identified and annotated metabolites, true; keep removable features and assign the tag for checking, true; replace true zero values with 1/10 of the minimum peak height over all samples, false. Lipid annotation was performed automatically using the in-silico MS/MS spectral library. Lipid normalization was performed based on the internal standard spiked, and the results displayed as

Normalized data matrix (Height).

Metabolomic analysis

The upper phase (aqueous phase) raw data were converted to open mzXML format using

MS Convert (Chambers, Maclean et al. 2012). MZmine version 2.53 was used to obtain the metabolite features (Pluskal, Castillo et al. 2010). For the identification of chemical families and annotated metabolite features the Global Natural Product Social Molecular Networking (GNPS) was used (Wang, Carver et al. 2016, Nothias, Petras et al. 2019). GNPS parameters used were; precursor and fragment ion mass tolerance: 0.02 Da; cosine score: >0.7; minimum 4 matched peaks; network topK: 10; maximum connected component size: 100; maximum shift between precursors: 500 Da; maximum Analog Search Mass Difference: 200 Da; filtering: remove all

MS/MS fragment ions within +/- 17 Da of the precursor m/z; retain only the top 6 fragment ions in a 50-Da window; row sum normalization; aggregate peak abundances per group: mean; run

60 DEREPLICATOR (Mohimani, Gurevich et al. 2017). Cytoscape (version 3.4.0) was used for the

Network visualization (Shannon, Markiel et al. 2003). Metabolite features common to blanks and to samples were removed (3X cutoff), and resulting metabolites normalized to total signal (TIC normalization). Principal coordinate analysis (PCoA) was performed on normalized data in a

QIIME1 environment and visualized using EMPeror (Caporaso, Kuczynski et al. 2010, Vazquez-

Baeza, Pirrung et al.). Metabolites differing between triatomine species were identified using

Random Forest in R, with 100 trees, and annotated from feature-based molecular networking results (Breiman 2001). Metabolite annotations are at confidence level 2–3 according to the 2007 metabolomics standards initiative (Sumner, Amberg et al. 2007).

Lipid nomenclature and abbreviations

According to the MS-Dial identification, the following abbreviations and nomenclature were used: ACar, acylcarnitine; Cer, ceramide; DAG, diacylglycerol; DGDG, digalactosyldiacylglycerol; DGTS, diacylglyceryltrimethylhomoserine; FA, free fatty acid; LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; LPI, lysophosphatidylinositol;

LPS, lysophosphatidylserine; LDGTS, lysodiacylglyceryltrimethylhomoserine; MGDG, monogalactosyldiacylglycerol; PL, phospholipid; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PI, phosphatidylinositol; SM, sphingomyelin; TAG, triacylglycerol.

Other abbreviations, a lowercase “e” was used to describe ether-linked lipid species, a “+O” designates an oxidized species.

Repository Data

The raw data has been deposited in MassIVE (http://massive.ucsd.edu/, accession #

MSV000085072 (negative mode) and MSV000085073 (positive mode)).

61 Molecular networking can be accessed at: https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=844c2ff8edf047218bd66f7c6c356ee8

(aqueous extraction, positive mode); https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=877f59ced7184f63a5d7faa0cbb1b525

(aqueous extraction, negative mode).

62 3.3 RESULTS

General description

Untargeted MS analysis was performed in the saliva of four triatomine species, T. lecticularia, M. pallidipennis, R. prolixus and P. herreri (collected as described in Methods) in positive- and negative-ion modes. Schematic representation of the methodology used is shown in

Fig. 3.1.

The total ion chromatograms (TIC) acquired in both positive- and negative-ion modes, using a C18 column, with a 32-min run, corresponding to the organic phase, and the TIC from the

C8 column, with a 7.5 min run, corresponding to the aqueous phase, can be seen in Fig. 3.2 and

Fig. 3.3, respectively. For the organic phase, a higher number of peaks were identified in the positive mode when compared with the negative (Fig. 3.2A and 3.2B). For the aqueous phase, the

TIC shows that most of the molecules eluted from the column between 0.2-0.3 min and 3.0-5.0 min in both modes (Fig 3.3).

Each biological replicate constituted of a pool of 10 insects. Three biological replicates from each species were ran in two technical replicates. In positive mode, the PCA plots of the organic phase showed some overlapping with T. lecticularia, M. pallidipennis, and P. herreri and a clear separation of the R. prolixus. The aqueous phase was analyzed by PCoA and the species T. lecticularia, M. pallidipennis, and P. herreri also cluster more closely than R. prolixus (Fig. 3.4A and C). In negative mode, better separation of samples can be seen in both, organic- and aqueous- phase (Fig. 3.4B and D).

63 Lipid characterization in triatomine saliva

Lipids identified with structural annotation supported by MS/MS spectra were considered for further analysis. In positive mode and in negative mode, 313 and 42 lipids were identified respectively. The identified lipids belonged to eighteen lipid classes and included free fatty acids

(FA), mono-, di- and triacylglycerols (MAG, DAG and TAG), eight phospholipid classes

(phosphatidylcholine, PC; phosphatidylethanolamine, PE; phosphatidylinositol, PI; phosphatidylserine, PS; lysophosphatidylcholine, LPC; lysophosphatidylethanolamine, LPE; lysophosphatidylinositol, LPI; and lysophosphatidylserine, LPS), sphingomyelin (SM), ceramide

(Cer), acylcarnitine (ACar), digalactosyldiacylglycerol (DGDG), diacylglyceryltrimethylhomoserine (DGTS), and its lyso-type form (LDGTS) (Table 3.1).

In positive mode, the TAG lipid had the highest number of individual lipid identified (205) followed by PC (36) and DAG (22) and in negative mode the highest was PE (12), followed by PI

(10) and LPE (6) (Table 3.1). The percentage of the total sum of the normalized data matrix

(Height) of each lipid class identified was evaluated and compared between the different saliva species (Fig. 3.7 A and B). Some lipid classes presented a closer percentage (~25%) among the different triatomines, such as DGTS and ACar in positive mode, and PI in negative mode. The lyso-species showed the highest percentage in P. herreri compared with the other species; fact observed in both modes. P. herreri also presented the highest percentage of the total PS identified

(45% and 43%, respectively in positive- and negative-mode). In R. prolixus, the highest percentages were detected with SM (34%), Cer (33%), DAG (49%), TAG (83%), and DGDG

(64%), all in positive mode. Another class that was higher in R. prolixus than in the other species was PE, having almost half of all the total amount detected (43% and 48%, respectively in positive- and negative-mode). In T. lecticularia, the highest percentages were detected with MAG (33%)

64 and LDGTS (49%), both in positive mode. In M. pallidipennis, the highest percentages were detected with PC (57% and 70%, respectively in positive- and negative-mode), and PI (64%, negative-mode).

Due to the relevance of LPC in the feeding process and parasite transmission as mentioned earlier, we focused on the lysophospholipid classes (lyso-PL) (Golodne, Monteiro et al. 2003,

Mesquita, Carneiro et al. 2008, Silva-Neto, Lopes et al. 2016). Lyso-PL with even and odd fatty acid chains were both identified, along with saturated and unsaturated bindings. The head group molecular structures of the lyso-PLs identified in this study can be found in Fig. 3.6. In total, eleven LPC, six LPE, one LPS, and one LPI were identified (see Fig. 3.7 for more details). Most of the lyso-PL were shared by all the four species, some presenting different amounts. The C15:0-

LPC was the only lyso-PL species-specific (detected only in P. herreri). In positive mode, the most abundant LPCs identified was the C16:0, and it was higher in R. prolixus; the C18:1 was higher in P. herreri and T. lecticularia, and C20:4 very high in P. herreri; the most abundant LPE was the C18:1 very high in P. herreri. In negative mode, the most abundant LPCs identified were the C18:1 higher in P. herreri; the most abundant LPE was the C18:1 higher in P. herreri and R. prolixus; and the C18:2 was high in P. herreri. The LPS detected was the C18:1 and the LPI

C20:4, both highly abundant in P. herreri.

Prostaglandins have been related to many activities that help the blood-feeding process such as vascular activity (vasodilation) and immunomodulation (i.e., downregulation of proinflammatory cytokines and upregulation of anti-inflammatory cytokines) (Bowman, Dillwith et al. 1996, Oliveira, Sa-Nunes et al. 2011, Poole, Mamidanna et al. 2013). Arachidonic acid (AA)

(C20:4) is the precursor for the synthesis of prostaglandins and was detected in all four triatomine species (Fig. 3.8). AA was detected in the form of lyso-species (~1.4 min), free FA(~2.7 min) and

65 phospholipids PI and PE (between 9 and 13 min) (Fig. 3.8 A). P. herreri presented the highest amount of lyso-PL with AA (Fig. 3.8 B). The AA was also found in different amounts in PI and

PE, with M. pallidipennis with the highest amount in these classes (Fig. 3.8 C).

A singly-charged species ([M+H]-) of a very long fatty acid chain (28:7) was also detected at m/z 409.311 and retention time of 8.4-8.5 min (Fig. 3.9 A-B). It was detected in all four species, and was more abundant in the R. prolixus and less in M. pallidipennis.

Metabolite characterization in triatomine saliva

The aqueous phase obtained was submitted to molecular networking for metabolite identification. With the approach applied 1,168 metabolite features were identified in positive-ion mode and 382 features in negative-ion mode, ranging from m/z 102.9554 to m/z 1278.7152. For the specific number of features identified in each species see Fig. 3.10. Most of the features were shared by all four triatomine species, 76% and 90%, respectively in positive- and negative-ion modes.

After molecular networking, the metabolites were grouped into 74 molecular families of at least 3 members (positive mode) and 21 molecular families of at least 3 members (negative mode).

These included purines and their derivatives, dipeptides, amino acids and their derivatives, phosphocholine family members, tricarboxylic acid cycle intermediates and acylcarnitines. The identification of some features was not possible due to the lack of annotations. Some chemical families are almost unique to a given species while others are shared. In positive mode, among the species-specific features, we identified the pyroGlu-Val-Arg tripeptide in M. pallidipennis and many dipeptides in P. herreri. In the negative mode, the only species-specific feature which we could annotate was oxidized glutathione in R. prolixus.

66 Random Forest (RF) algorithm was used to rank the top 30 metabolomic features displaying the highest differential between species. Most were not annotated. In positive mode, many dipeptides were identified and were elevated in P. herreri. Phenylalanine was also identified to be highly abundant in P. herreri. In negative mode, xanthine was higher in P. herreri and R. prolixus and acetyl-CoA higher in T. lecticularia.

The presence of adenosine in tick saliva has been related with a potent anti-inflammatory response (Oliveira, Sa-Nunes et al. 2011). Due to this, the presence of adenosine and other purines have been here investigated. Here, we identify and report for the first time in triatomine saliva the purines adenosine, guanosine, and AMP (Fig. 3.11). The presence of adenosine was highly abundant in R. prolixus (Fig. 3.12 A). Guanosine was lower in M. pallidipennis and AMP lower in P. herreri (Fig. 3.12 B-C).

Figure 3.1. Schematic representation of the methodology used for extraction.

The samples were resuspended in water, along with 5 volumes of cold chloroform-methanol

(2:1[vol/vol]) solution, incubated for 5 min on ice, subjected to vortex mixing for 1 min, and centrifuged at 13,400 xg for 10 min at 4°C to obtain a two-phase system: lower (organic) and upper

(aqueous). Both phases were dried under N2 steam and stored at −20°C until use. The organic phase was subjected through a C18 column, the aqueous phase through a C8 column and the compounds were analyzed by the softwares MS-Dial, MZmine and GNPS.

Figure 3.2. Comparison between the organic phases from four different triatomine species in positive- (A) and negative-modes

(B).

After the total lipid extraction, the organic phases were subjected to LC-MS/MS (C18 column) into a QE-plus and analyzed in both modes, positive (A) and negative (B), 32 min run as described in methods. The graphs show the total-ion chromatogram (TIC).

Figure 3.3. Total ion chromatogram (TIC) of aqueous phase in positive- (A) and negative-modes (B).

After the total lipid extraction, the aqueous phases were subjected to LC-MS/MS (C8 column) into a QE-plus and analyzed in positive-

(A) and negative-modes (B), 7.5 min run, as described in Methods. The graphs show the total-ion chromatogram (TIC).

Figure 3.4. Principal component analysis (PCA) of identified lipids and principal coordinate analysis (PCoA) of metabolites in positive- and negative-modes.

Two-dimensional PCA of organic phase in positive- (A) and negative-modes (B) were generated by MS-Dial, using just lipids with structural annotation supported by MS/MS spectra; scale method: auto scale; transform method: Log 10. Three-dimensional PCoA of aqueous phase positive-(C) and negative-modes (D) were generated in QIIME1 and visualized using EMPeror.

Figure 3.5. Comparison of the lipid classes percentage identified by MS-Dial between the different triatomine species.

The graph shows the comparison in percentage of each lipid class based on the sum of the total normalized data matrix (height) after lipid identification and normalization by MS-Dial. FA: free fatty acids. MAG: monoacylglycerol. DAG: diacylglycerol. TAG: triacylglycerols. PC: phosphatidylcholine. PE: phosphatidylethanolamine. PI: phosphatidylinositol. PS: phosphatidylserine. LPC: lysophosphatidylcholine. LPE: lysophosphatidylethanolamine. LPI: lysophosphatidylinositol. LPS: lysophosphatidylserine. SM: sphingomyelin. Cer: ceramide. ACar:

72 acylcarnitine. DGDG: digalactosyldiacylglycerol. DGTS: diacylglyceryltrimethylhomoserine.

LDGTS: diacylglyceryltrimethylhomoserine.

Figure 3.6. Molecular structures of lyso-PLs identified in this study.

The molecular structures of the head group are highlighted by the red box. The FA chains are indicated on the right. The lipids structures are taken from MS-Dial structure and nomenclature database. LPC, lysophosphatidylcholine; LPE, lysophosphatidylethanolamine; LPI, lysophosphatidylinositol; LPS, lysophosphatidylserine.

Figure 3.7. Lysophospholipids identified in the triatomine saliva in positive- and negative- modes.

After lipid identification by MS-Dial, the lysophospholipids were compared between the four- triatomine species. Lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE) were identified in both modes. Moreover, in negative the lysophosphatidylinositol (LPI) and lysophosphatidylserine (LPS) were also identified.

Figure 3.8. Arachidonic acid (C20:4) identification in negative mode.

After the total lipid extraction, the organic phase was subjected to LC-MS/MS using a C18 column coupled to the QE-Plus and analyzed in negative mode and the base peak of 303.232 m/z, corresponded to the Arachidonic acid (C20:4) highlighted (A). After the identification by MS-

Dial, the lipids with fatty acid chain with 20:4 were chosen. The graph (B) show the lyso-species and the free fatty acids, and (C) the phospholipid class. FA: free fatty acid. LPC: lysophosphatidylcholine. LPE: lysophosphatidylethanolamine. LPI: lysophosphatidylinositol.

Figure 3.9. Identification of very-long chain fatty acids (C28:7) in the triatomine saliva.

After the total lipid extraction, the organic phase was subjected to LC-MS/MS using a C18 column coupled to the QE-Plus and analyzed in negative mode and the base peak of 409.311 m/z, corresponded to very-long chain fatty acids (C28:7) highlighted (A). The graph (B) show the full mass of the peak in RT: 8.57 min, and the molecular structure according to the National Center for

Biotechnology Information. PubChem Database. CID=14647893, https://pubchem.ncbi.nlm.nih.gov/compound/14647893 (accessed on Feb. 26, 2020). Panel (C) shows the comparison of the normalized data matrix (height) of the FA 28:7 identified in the four triatomine saliva by MS-Dial. RT: retention time.

Figure 3.10. Comparison of the metabolic features identified in the triatomine saliva.

After the total lipid extraction, the aqueous phase was subjected to LC-MS/MS using a C8 column coupled to the QE-Plus and analyzed using MZmine and molecular networking. The Venn diagram

(A) correspond to the positive mode and (B) to negative mode.

Figure 3.11. Molecular network of the purines identified in the triatomine saliva.

Each circle (=node) is one metabolite feature. Nodes connected to each other (by edges=lines) represent structurally-related features (=chemical family). Pie chart indicate relative feature abundance between species. Labels are the feature annotations.

Figure 3.12. Identification of purines in triatomine saliva.

After the total lipid extraction, the aqueous phase was subjected to LC-MS/MS using a C8 column coupled to the QE-Plus and analyzed using MZmine and molecular networking. The graph (A) show the adenosine peak area, (B) guanosine peak area and (C) AMP peak area. Non-overlapping notches indicate statistically significant differences in peak area.

80 Table 3.1. Summary of number of lipid identified.

Summary of lipid class found Number of lipids per class Nomenclature Ontology M. paliidipennis P. herreri R. prolixus T. lecticularia Positive mode Triacylglycerol TAG 187 191 204 187 Phosphatidylcholine PC 36 34 31 36 Diacylglycerol DAG 22 22 22 22 Phosphatidylethanolamine PE 17 16 16 15 Lysophophatidylcholine LPC 9 11 10 10 Lysophosphatidylethanolamine LPE 4 5 5 5 Sphingomyelin SM 5 5 5 5 Ceramide Cer 2 2 2 2 Diacylglyceryl trimethylhomoserine DGTS 2 2 2 2 Monoacylglycerol MAG 2 2 2 2 Phosphatidylinositol PI 2 2 2 2 Acylcarnitine ACar 1 1 1 1 Digalactosyldiacylglycerol DGDG 1 1 1 1 Lysodiacylglyceryl trimethylhomoserine LDGTS 1 1 1 1 Phosphatidylserine PS 1 1 1 1 Negative mode Phosphatidylethanolamine PE 12 12 12 12 Phosphatidylinositol PI 8 9 9 9 Lysophosphatidylethanolamine LPE 3 6 6 5 Fatty acid FA 5 5 5 5 Lysophophatidylcholine LPC 2 4 4 3 Lysophosphatidylserine LPS 1 1 1 1 Phosphatidylserine PS 1 1 1 1 Lysophosphatidylinositol LPI 0 1 1 0 Phophatidylcholine PC 2 2 2 2

Number of lipids per class Nomenclature Ontology M. pallidipennis P. herreri R. prolixus T. lecticularia Positive mode Triacylglycerol TAG 187 191 204 187 Phosphatidylcholine PC 36 34 31 36 Diacylglycerol DAG 22 22 22 22 Phosphatidylethanolamine PE 17 16 16 15 Lysophosphatidylcholine LPC 9 11 10 10 Lysophosphatidylethanolamine LPE 4 5 5 5 Sphingomyelin SM 5 5 5 5 Ceramide Cer 2 2 2 2 Diacylglyceryl trimethylhomoserine DGTS 2 2 2 2 Monoacylglycerol MAG 2 2 2 2 Phosphatidylinositol PI 2 2 2 2 Acylcarnitine ACar 1 1 1 1 Digalactosyldiacylglycerol DGDG 1 1 1 1 Lysodiacylglyceryl trimethylhomoserine LDGTS 1 1 1 1 Phosphatidylserine PS 1 1 1 1 Negative mode Phosphatidylethanolamine PE 12 12 12 12 Phosphatidylinositol PI 8 9 9 9 Lysophosphatidylethanolamine LPE 3 6 6 5 Fatty acid FA 5 5 5 5 Lysophosphatidylcholine LPC 2 4 4 3 Phosphatidylcholine PC 2 2 2 2 Lysophosphatidylserine LPS 1 1 1 1 Phosphatidylserine PS 1 1 1 1 Lysophosphatidylinositol LPI 0 1 1 0

82 3.4 DISCUSSION

Despite the increase in the discovery of new molecules in triatomine saliva, deeper comprehensive lipidomic and metabolomic studies are still incipient. Here, we conducted the first in-depth high-resolution comparative lipidomic and metabolomic analyses in the saliva of four triatomine species, two from North America (T. lecticularia, and M. pallidipennis) and two from

South America (R. prolixus and P. herreri).

Hematophagous vectors can successfully complete a blood meal due to the bioactive molecules present in the saliva. Most of the molecules described so far are proteins and include analgesics, anti-hemostatic (vasodilators, anti-platelets, anti-coagulants), anti-inflammatory and immunomodulators (Fontaine, Diouf et al. 2011, de Araujo, Bussacos et al. 2012, Santiago, de

Araujo et al. 2020).

Here, different lipid classes were identified, and although the intensity it might be different, all the lipid classes were identified in all the triatomine species evaluated in this study. The highest number of individual lipids identified was TAG which are useful for energy storage and can be very important for the salivary gland cells during the feeding process due to the high demand in producing and releasing the molecules in the saliva. Fatty acids, obtained after a blood meal, are used for the synthesis of the different lipid classes, such as TAG and PL (Gondim, Atella et al.

2018). The lipids are exported from the gut to other organs with the participation of a lipophorin. de novo synthesis of FA can also occur. Insights into the R. prolixus genome allowed the identification of few proteins involved in the de novo synthesis of lipids (Majerowicz, Calderon-

Fernandez et al. 2017).

83 Besides the classical function of lipids, like energy storage and structural roles in membranes, another important part of lipids are their function as potent bioactive signaling mediators. During the feeding process, the lipids present in the saliva can be fundamental players in the interface vector-host, such as the PL-derived substrates, DAG and arachidonic acid, that can interfere with both, hemostatic and immune system (Nishizuka 1992, O'Donnell, Rossjohn et al.

2018).

Undergo phospholipases action, lyso-PLs are generated and are a major bioactive lipid. In the feeding context, due to the anti-hemostatic properties, LPC can play an essential role (Golodne,

Monteiro et al. 2003). LPC has been reported in R. prolixus and T. infestans saliva (Golodne,

Monteiro et al. 2003, Lima, Carneiro et al.). LPC also induces cell chemotaxis, immunosuppression of NO production, and increases the rate of association of T. cruzi with macrophages which ultimately increases parasitemia (Mesquita, Carneiro et al. 2008, Silva-Neto,

Carneiro et al. 2012). Here, we showed that lyso-PLs were highly abundant in P. herreri. In the previews study, P. herreri saliva modulated dendritic cells by powerfully stimulating the production of IL-10, an anti-inflammatory cytokine (Mendes, Carvalho-Costa et al. 2016). We speculate that the higher presence of lysoPCs when compared with the other species have an influence in this aspect.

In addition to an increase in association of T. cruzi and macrophages, another action of the

LPC is the ability to increase the parasite growth inside of the triatomine gut (Chagas-Lima, Pereira et al. 2019). The effect was observed with different fatty acyl chains, such as C18:0, C16:0, or

C18:1 LPC. In this study, the most abundant LPC were C16:0 and C18:1. Therefore, besides being present in the blood, these LPC is also present in the saliva, which can also be sucked up by the

84 insect, together with blood (Soares, Carvalho-Tavares et al. 2006). Consequently, the LPC present on the saliva can also have an influence in the increase of parasite growth.

Each lipid is formed by different FA length that can be saturated or not, (O'Donnell,

Rossjohn et al. 2018), ultimately reflecting in their functions. While the LPC C18:1 showed activity similar to the platelet-aggregating factor (PAF), other LPC species, C16:0, C18:0, and

C18:2 failed to do so (Gazos-Lopes, Oliveira et al. 2014). Anteriorly, in the saliva, only the LPC

C16:0 (palmitic acid) had been characterized (Mesquita, Carneiro et al. 2008). Here, besides LPC

C16:0, we identified several other FA.

Prostaglandin (PGE2) is a powerful immunoactive molecule present in different vectors saliva (Ribeiro, Makoul et al. 1985, Carregaro, Valenzuela et al. 2008, Poole, Mamidanna et al.

2013). It has the ability to increase vasodilation and decrease inflammation by regulating cytokine production (Carvalho-Costa, Mendes et al. 2015). Similar effects were observed with triatomine saliva but the presence of PGE2 has not been described so far (Mendes, Carvalho-Costa et al.

2016). Arachidonic acid (C20:4) is the precursor for the synthesis of prostaglandins (Hanna and

Hafez 2018) and was detected in all four triatomine species.

A very-long-chain FA was also detected. Very-long-chain FAs are found in higher plants and animals, such as seed oils, plant waxes, hair, wax-like glands, brain and liver and in some lower organisms such as microalgae, fungi, and bacteria (Kihara 2012). In insects, very-long-chain fatty acids can be found for instance in the cuticle (Golebiowski, Bogus et al. 2011).

Although no metabolomic studies have been performed in the triatomine saliva, it has been done in fecal samples (Antunes, Han et al. 2013). Fatty acids, steroids, glycerolipids, nucleotides, and sugars were uniformly found in all three species evaluated. Whereas prenol lipids, amino acids, glycerolipids, steroids, phenols, fatty acids and derivatives, benzoic acid and derivatives presented

85 variable frequencies (Antunes, Han et al. 2013). Here, most of the metabolites features were shared by all four triatomine species.

Adenosine is a potent anti-inflammatory salivary inhibitor of DCs. Here, we identify adenosine, guanosine, and AMP for the first time in triatomine saliva. Adenosine has also been identified in tick saliva (Oliveira, Sa-Nunes et al. 2011). It is known that adenosine is a purine that modulates a variety of immunologic functions, such as cytokine production by DCs (Hasko and

Cronstein 2004, Oliveira, Sa-Nunes et al. 2011). Here, it was highly abundant in R. prolixus.

In conclusion, we describe for the first time, in triatomine saliva many non-protein compounds, with potential immunomodulatory action. Taken together, our results support the concept that the salivary molecules counteract most of the host defenses, hemostatic and immune system response, helping the triatomine in the feeding process and as a secondary effect, increasing the T. cruzi infection.

86 Chapter 4: Final conclusions and future directions

4.1 OVERVIEW AND FINAL CONCLUSIONS

The main purpose of this study was to gain insight into the saliva composition from four triatomine species emphasizing the molecules with potential immune effects. The feeding process of hematophagous vectors imposes to the saliva molecules different evolutionary pressures. These dynamic vector-host interactions might have induced each species to produce and secrete distinct bioactive salivary molecules. In this study, we evaluated the saliva of two triatomines from North

America and two from South America.

Regardless of which omics approach we employed, no clustering concerning geographical origin was detected. It was evident that independent of the data set, R. prolixus tends to always cluster apart from the other three species. This observation follows the division of the subfamily

Triatominae into tribes; R. prolixus belongs to the tribe Rhodniini and the other three species T. lecticularia, P. herreri, and M. pallidipennis to the tribe Triatomini (Justi and Galvao 2017).

The triatomine R. prolixus is the first non-dipteran insect vector to have the genome sequenced and it is the model organism for the study of triatomine physiology (Mesquita, Vionette-

Amaral et al. 2015, Nunes-da-Fonseca, Berni et al. 2017). Our results make us question if this species is the best model organism for all triatomines.

Our results revealed that just around 3% of the secreted proteins are shared by all four species whereas all the lipid classes are detected in all four triatomines and more than 70% of the metabolites are shared by all four. Thus, the proteome data, specifically the secreted proteins, are more species-specific than the non-proteomic data. This indicates a much higher evolution pressure on the secreted proteins and a more conservative lipidomic and metabolomic profile.

87 We were also able to show that the salivary antigens can be used as biomarkers of triatomine bites. Although more experiments are needed to identify the exact molecules responsible for the antibody production, we were able to show a clear separation in the identification between those who have been exposed to those who have not. Therefore, the salivary antigens can be a useful tool for the identification of population at risk to measure the prevalence and intensity of infestations, and search for unique or multiple species in the same area, to detect re-emerging insects and provide an indicator of autochthone transmission.

Here, we also describe for the first time the presence of EVs in the triatomine saliva. EVs are significant components in the communication between vector-host cells (Wu, Wang et al.

2018). We investigated just the proteins in the EVs, but the cargo can contain lipids and metabolites, as well. Due to the drastic change, for instance in pH, from saliva to host skin, EVs seem to be an effective way to carry more sensible molecules to the host targets.

The lipids existing in the saliva can be originated from the blood ingestion or de novo synthesis. We found the following proteins related to the lipid metabolism: carboxylic ester hydrolases, acetyl-CoA, esterases, and lipases. Since the blood is not a rich source of lipids, it is interesting that they have alternatives.

Previously, it has been shown that the triatomine saliva can immunomodulate DCs and that depending on the triatomine species this effect is more or less intense. One of the effects is to increase the production of the cytokine IL-10 and to inhibit the production of pro-inflammatory cytokines. Similar effects have been shown in tick saliva and the molecules responsible are PGE2 and adenosine. Here, we demonstrate the first evidence that the triatomine saliva also has adenosine and possibly PGE2 as well, due to the presence of its precursor, C20:4.

88 All triatomine species are considered potential transmitters of the parasite. A group of factors makes some species more effective than others, such as the duration of feeding and saliva composition. However, assuming that the species “X” in more powerful than “Y” based in the presence or absence of one molecule or a group of molecules is reckless. The saliva is a cocktail of redundant molecules, so even if one molecule is more expressed in “X” than in “Y”, it does not mean that “X” is more powerful. The result of the effects is obtained by the sum of all molecules present in the saliva. Thus, to show which species saliva would be more effective in the T. cruzi infection in vivo, specific experiments would need to be performed.

In conclusion, we described many proteins and non-protein compounds with potential immunomodulatory effects, which support the concept that salivary molecules counteract most of the host defenses, hemostatic and immune system response, helping the triatomine in the feeding process and possibly increasing T. cruzi infection.

89 4.2 FUTURE DIRECTIONS

Although systems biology or omics studies provide significant insights into the saliva composition, we still have a lot to explore. At present, we still missing the functional role of a considerable number of molecules due to the lack of annotation. Moreover, the lack of a species- specific database for protein identification underestimates the number of species-specific proteins.

Beyond the descriptive aspect of the saliva composition, many points still to be investigated. One point that has not been explored so far is if the saliva from different species of triatomine would alter the outcome of the disease. In vitro, the effect of the saliva tested against

DCs were able to increase the association of T. cruzi in three out of the four species tested (Mendes,

Carvalho-Costa et al. 2016). In this study, the only exception was with R. prolixus. In the end, a greater association of parasite and cells could mean more parasitemia, which could lead to more severe disease. Therefore, this could lead us to the following assumption, the more immunomodulatory the saliva is, the more severe the disease would be.

When comparing in vitro experiments with what is happening in vivo, an aspect we should observe is the fact that in vivo context, other cells are also present. Thus, even if the saliva of a specific species modulates very strongly one type of cell, for instance, attracting more of that type of cell to the bite site, it does not mean that the other species could not do the same for a different type of cell. In the end, even attracting different immune cells could result in the same increase of infection. Although R. prolixus was not able to increase the association of T. cruzi on DCs, another study showed that this species was able to increase the association of T. cruzi on macrophages

(Mesquita, Carneiro et al. 2008). Therefore, what if the attraction of different types of cells results in a different environment in the bite site and the presence of the different cells influence how the

90 T. cruzi would be spread in the host system, infecting different tissues. This could influence the clinical aspect, leading to different pathology, to the cardiac, digestive or indeterminate form.

In addition to the parasite T. cruzi, the triatomines, mainly in the genus Rhodnius, can also transmit the parasite Trypanosoma rangeli (Azambuja and Garcia 2005). Differently from T. cruzi,

T. rangeli is transmitted by the saliva. Some pieces of evidence suggest that R. prolixus seems to impair the development and transmission of some strains of T. rangeli (Pulido, Perez et al. 2008).

We know that depending on the region, some T. cruzi strains can be more prevalent than others.

What if the triatomine species present in that region favors some of the T. cruzi strains more than others? Do some triatomine species transmit some T. cruzi strains better than others do?

The T. rangeli can also manipulate the saliva composition to favor its transmission. It is been shown that T. rangeli decreases the number of salivary molecules, making it difficult to feed and increasing the amount of probing, which also increases the chances to transmit the parasite

(Garcia, Mello et al. 1994). The salivary composition in T. cruzi-infected bugs has not been studied. What if the parasite T. cruzi is also able to manipulate the expression of salivary molecules? In this case, maybe T. cruzi would do the opposite of the T. rangeli. Instead of decreasing the presence of some molecules, it might increase it. As a result, the feeding would be improved and the chances to start defecating while still in the host would be also increased. In summary, the research of triatomine saliva is a field in ascension and lots of open questions still to be answered.

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105 Appendix

LIST OF ABBREVIATIONS

5’NUC 5' nucleotidase

AA Arachidonic acid

ACar Acylcarnitine

ACE Angiotensin-converting enzymes

Ag Antigen

Ag5 Antigen-5-like proteins

AMP Adenosine monophosphate

BCA Bicinchoninic acid

BSA Bovine serum albumin

CAN Acetonitrile

CBB Carbonate-bicarbonate buffer

Cer Ceramide

ChD Chagas disease

ChHSP Chagas human serum pool

CL-ELISA Chemiluminescent ELISA

DAG Diacylglycerol

DBD Database-dependent

DBI Database-independent

DC Dendritic cell

106 DGDG Digalactosyldiacylglycerol

DGTS Diacylglyceryltrimethylhomoserine

DTT Dithiothreitol

ELISA Enzyme-linked immunosorbent assay

ER Endoplasmic reticulum

EVs Extracellular vesicles

FA Free fatty acid

FASP Filter-Aided Sample Prep

FT-sal Flow-through saliva

GNPS Global Natural Product Social Molecular Networking

HRP Horseradish peroxidase

IAA Iodoacetamide

IDs Identification

IgG Immunoglobulin G

KB Knowledge base

LC-MS Liquid chromatography-tandem mass spectrometry

LDGTS Lysodiacylglyceryltrimethylhomoserine

LPC Lysophosphatidylcholine

LPE Lysophosphatidylethanolamine

LPI Lysophosphatidylinositol

LPS Lysophosphatidylserine lyso-PLs Lysophospholipids

MAG Monoacylglycerols

107 MGDG Monogalactosyldiacylglycerol

MS/MS Tandem mass spectrometry

MW Molecular weight

N2 Nitrogen

NCBI National Center for Biotechnology Information

NGP24b Neoglycoprotein of structure Galα1,3Galβ1,4GlcNAcα-BSA

NHSP Normal human serum pool

NO Nitric oxide

NP Nitrophorin

NR Non-redundant protein database

NTA Nanoparticle tracking analyses

OBP Odorant-binding protein

PA Phosphatidic acid

PAF Platelet-activating factor

PBS Phosphate-buffered saline

PBST Phosphate-buffered saline with Tween® detergent

PC Phosphatidylcholine

PCA Principal component analysis

PCoA Principal coordinate analysis

PE Phosphatidylethanolamine

PGE2 Prostaglandin

PI Phosphatidylinositol

PL Phospholipid

108 QE Plus-MS QE-Plus Orbitrap mass spectrometer

RF Random Forest

RLU Relative luminescence units

SDS–PAGE Sodium dodecyl sulfate–polyacrylamide gel electrophoresis

SM Sphingomyelin

TAG Triacylglycerol

TIC Total ion chromatograms

TLC Thin-layer chromatography

TLR Toll-like receptor

UF-sal Ultra-filtrated saliva

109 TRIATOMINES: LABORATORY MAINTENANCE AND SALIVA COLLECTION

Maintenance of insects in the insectary

Figure 1. In the insectary, the insects are kept on plastic pots closed at the top with a fine fabric.

Inside the pot, a paper holder with holes is placed to serve as support and to give access to the meal source. The pots are kept on shelves lined with white paper. To prevent ants from climbing up, the legs of the shelves are placed in containers with oil.

110 Feeding process

Figure 2. The insects are feed weekly in immobilized chickens. The feeding takes place in an appropriate table with holes. The length of the feeding depends in how much full the container with the triatomines is, and usually terminated when most of the insects look full. Separate from the feeding times, the chickens are kept in an appropriate place with water and specific feed.

Insecticides or other products for controlling insects or lice should not be used because they can cause the death of the triatomines.

111 Salivary glands collection

Figure 3. The extraction of the salivary glands was done according to the triatomine species. The triatomine R. prolixus had their heads pulled out with forceps, allowing exposure of the salivary glands and their collection. Their salivary glands are red due to the presence of the protein

Nitrophorin.

112

Figure 4. To collect the glands of the other three species (P. herreri, M. pallidipennis, T. lecticularia), the side of the abdomen and chest were sectioned and through the aid of a stereoscopic microscope and tweezers, the glands were located and collected.

113 LIST OF PUBLICATIONS AND MANUSCRIPTS

19. Mendes, M.T.; et al. In-depth high-resolution proteomic analysis of triatomines saliva from distinct geographical locations reveals substantial differences in their proteome profiles and immunoreactivity. To be submitted soon to Molecular Systems Biology. 2020. (In preparation).

18. Mendes, M.T.; et al. Triatomine saliva lipidomic and metabolomics: identification of non-protein compounds with possible immune effect in the mammalian host. To be submitted soon to mSystems. 2020.

(In preparation)

17. Fajardo, E. *; Mendes, M.T. *; et al. Proteomics for discovery of genotype-specific and universal biomarkers for the accurate diagnosis of Chagas disease. *These authors contributed equally to this work. To be submitted soon to PNAS. 2020. (In preparation)

16. Karimi, N.; ...Mendes, M.T.; et al. Isolation and characterization of-Gal-Containing extracellular vesicles (EVs) from three major genotypes of Trypanosoma cruzi: potential biomarkers of Chagas disease.

To be submitted soon. 2020.

15. Estevao I.*, Ortega-Rodriguez, U.*, ...Mendes, M.T.; et al. Epidemiological assessment of Chagas disease in El Paso Texas region. To be submitted soon. 2020. (*Co-first authors)

14. Torrico, F.; Gascon, J.; Barreira, F.; Blum, B.; Almeida, I.C.; Alonso-Vega, C.; Barboza, T.; Bilbe, G.;

Correia, E.; Garcia, W.; Ortiz-Daza, L. Parrado, R.; Ramirez, J. C.; Ribeiro, I.; Strub-Wourgaft, N.;

Vaillant, M.; Sosa-Estani For The Bendita Study Group. Randomized trial of

Benznidazole/Fosravuconazole for Chronic Chagas Disease. To be submitted soon to New England J

Medicine. 2020.

114

13. Cortes-Serra, N.; Mendes, M.T.; Mazagatos, C.; Segui-Barber, J.; Ellis, C. C.; Ballart, C.; Garcia-

Alvarez, A.; Gallego, M.; Gascon, J.; Almeida, I. C.; Pinazo, M. J.; Fernandez-Becerra, C. Plasma-derived extracellular vesicles as potential biomarkers in a heart transplant patient with chronic Chagas disease.

Emerging Infectious Diseases. 2020, accepted on March 30, 2020.

12. Franzim-Junior, E.; Mendes, M.T.; Anhê, A.C.B.M.; Costa, T. A. Da; Silva, M.V.; Hernadez, C.G;

Pelli, A.; Sales-Campos, H.; Oliveira, C.J.F. Biology of Meccus pallidipennis (hemiptera: reduviidae) to other conditions than that encountered in their native habitat. J Arthropod Borne Dis. 2018 Sep; 12(3): 262–

268.

11. Ribeiro, K.S.; Vasconcellos, C.I.; Soares, R.P.; Mendes, M.T.; Ellis, C.C.; Aguilera-Flores, M.;

Almeida, I. C.; Schenkman, S.; Iwai, L.K.; Torrecilhas, A.C. Proteomic analysis reveals different composition of extracellular vesicles released by two Trypanosoma cruzi strains associated with their distinct interaction with host cells. J Extracell Vesicles. 2018 Apr 17;7(1):1463779.

10. Nevoa, J.C.; Mendes, M.T.; Silva, M.V.; Soares, S.C.; Oliveira, C.J.F.; Ribeiro, J.M.C. An insight into the salivary gland and fat body transcriptome of Panstrongylus lignarius (Hemiptera: Heteroptera), the main vector of Chagas disease in Peru. PLoS Negl Trop Dis. 2018 Feb 20;12(2):e0006243.

9. Franzim-Junior, E.; Mendes, M.T.; Anhê, A.C.B.M.; Pelli, A.; Silva, M.V.; Rodrigues Junior V.; Sales-

Campos, H.; Oliveira, C.J.F. Panstrongylus herreri and its ability to develop under fluctuating environmental conditions. Rev Soc Bras Med Trop. 2017 May-Jun;50(3):436.

8. Carvalho-Costa, T.M.; Mendes, M.T.; Da Silva, M.V.; Rodrigues, V.; Bruschi Thedei, G.C.M.; Oliveira,

C.J.F.; Thedei, G.J.R. Light-Emitting Diode at 460 ± 20 nm Increases the Production of IL-12 and IL-6 in

115 Murine Dendritic Cells. Photomed Laser Surg. 2017 Oct;35(10):560-566.

7. Franzim-Junior, E., Mendes, M.T.; Anhê, A.C.B.M; Pelli, A.; Silva, M.V.; Rodrigues, V.; Sales-

Campos, H.; Oliveira, C.J.F. The development of Panstrongylus herreri under fluctuating environmental conditions. Rev Soc Bras Med Trop. 2017 Jan-Feb;50(1):121-125.

6. Mendes, M.T.; Carvalho-Costa, T.M,; Da Silva, M.V.; Anhê, A.C.B.M.; Guimarães, R.M., Da Costa,

T.A.; Ramirez, L.E.; Rodrigues, V.; Oliveira, C.J. Effect of the saliva from different triatomine species on the biology and immunity of TLR-4 ligand and Trypanosoma cruzi-stimulated dendritic cells. Parasite

Vectors. 2016 Dec 9;9 (1):634.

5. Montandon, C.E.; Barros, E.; Vidigal, P.M.; Mendes, M. T.; Anhê, A.C.; De Oliveira Ramos, H.J.; De

Oliveira, C.J.; De Siqueira, C.L. Comparative proteomic analysis of the saliva of the Rhodnius prolixus,

Triatoma lecticularia and Panstrongylus herreri triatomines reveals a high interespecific Functional

Biodiversity. Insect Biochem Mol Biol. 2016 Apr;71:83-90.

4. Montandon, C.E.; Barros, E.; Vidigal, P.M.; Mendes, M. T.; Anhê, A.C.B.M.; De Oliveira Ramos, H.J.;

De Oliveira, C.J.; De Siqueira, C.L. Development of data for the identification and characterization of proteins found in Rhodnius prolixus, Triatoma lecticularia and Panstrongylus herreri. Data Brief. 2016

Mar 19;7:844-7.

3. Carvalho-Costa, T.*; Mendes, M. T.*; Da Silva, M. V.; Da Costa, T.; Tiburcio, M.; Anhê, A.C.B.M.;

Rodrigues, V.; Oliveira, C.J.F. Immunosuppressive effects of Amblyomma cajennense tick saliva on murine bone marrow-derived dendritic cells. Parasites & Vectors., v.8, p.22 - , 2015. *These authors contributed equally to this work.

116 2. Vazquez, B. P.; Vazquez, T. P.; Miguel, C. B.; Rodrigues, W. F.; Mendes, M. T.; Oliveira, C.J.F.; Chica,

J. E. L. Inflammatory responses and intestinal injury development during acute Trypanosoma cruzi infection are associated with the parasite load. Parasites & Vectors., v.8, p.1 - 12, 2015.

1. Da Costa, T. A.; Silva, M. V.; Mendes, M. T,; Carvalho-Costa, T. M.; Batista, L. R.; Lages-Silva, E.;

Rodrigues, V.; Oliveira, C. J.; Ramirez, L. E. Immunomodulation by Trypanosoma cruzi: Toward

Understanding the Association of Dendritic Cells with Infecting TcI and TcII Populations. J IMMUNOL

RES., v.2014, p.1 - 12, 2014.

117 Curriculum vitae

Maria Tays Mendes graduated from the Federal University of Triangulo Mineiro (UFTM),

Uberaba, Brazil, in 2011, where she pursued a bachelor’s degree in Biomedicine. While pursuing her bachelor’s degree, she joined a microbiology lab and then a parasitology lab. In 2014, she acquired a Master’s of Science degree in Tropical Medicine and Infectious disease with application in Immunology and Parasitology from the Federal University of Triangulo Mineiro. Also in 2014, she was awarded with the Brazilian Scholarship Science Without Borders, and she joined the doctoral program in Biological Sciences at the University of Texas at El Paso (UTEP), El Paso,

Texas, where she has been working under the supervision of Dr. Igor C. Almeida.

She has participated in several conferences including the Second Border Biomedical

Research Center Symposium Health Disparities: From Molecules to Disease (2015), Rio Grande

Branch of American Society for Microbiology (2016, 2017), and the Tropical Infectious Diseases

Gordon Research Seminar (GRS) and Conference (GRC) (2017 and 2019).

In addition, she has been the recipient of the awards Dodson Research Grant (2017),

Graduate School Travel Grant (2017), Biological Science Dodson Travel Grant (2017), Biological

Science Travel Grant (2019), Graduate School Summer Research Grant (2019), and The Allien and Paul C. Davidson Scholarship (2019). She has already published twelve peer-reviewed papers, ten as co-author and two as the first author. Soon she will publish three articles as the first author.

After graduation, she will work as a post-doctoral fellow at the University of Maryland in

Baltimore, MD.

E-mail: [email protected]. This dissertation was typed by Maria Tays Mendes.

118