Anopheles albimanus natural microbiota is altered within one generation of laboratory colonization

Research on mosquito-microbe interactions may lead to new tools for mosquito and mosquito-borne disease control. To date, such research has largely utilized laboratory-reared mosquitoes that typically lack the microbial diversity of wild populations. A logical progression in this area involves working under controlled settings using field-derived mosquitoes or, in most cases, their progeny. Thus, an understanding of how laboratory colonization affects the assemblage of mosquito microbiota would aid in advancing mosquito microbiome studies and their applications beyond laboratory settings. Using high throughput 16S rRNA amplicon sequencing, we characterized the internal and cuticle surface microbiota of F1 progeny of wild-caught adult Anopheles albimanus from four locations in Guatemala. A total of 132 late instar larvae and 135 2-5day old, non-blood-fed virgin adult females that were reared under identical laboratory conditions, were pooled (3 individuals/pool) and analyzed. F1 larvae from different maternal sites showed different microbial compositions (p=0.001; F = 9.5), but these differences were absent at the adult stage (p=0.12; F =1.6). These results suggest that field-acquired mosquito microbiota may be lost in as early as the first generation of colonization under normal laboratory conditions, thus, requiring adjustments to maintain field-derived microbiota. This is the first time that the microbiota of F1 progeny of wild-caught mosquitoes has been characterized in relation to maternal collection site. Our findings provide a comprehensive background for studying how parentage and environmental conditions differentially or concomitantly affect mosquito microbiome composition, and how this can be exploited in advancing mosquito microbiome studies and their applications beyond laboratory settings.

competence-the mosquito's ability to acquire, maintain and transmit pathogens [5]. These 52 effects on multiple physiological characteristics are being leveraged to develop novel 53 approaches to fight mosquito-borne diseases [9]. 54 The use of next generation molecular biology tools has resulted in extensive characterization of 55 mosquito microbiota, with the initial focus on bacterial and archaeal components now expanding 56 to eukaryotic microbes [10, 11] and viruses [12,13]. These advances in mosquito microbiota 57 research have led to field applications of mosquito symbionts for mosquito control. For Aedes 58 aegypti, the principal vector of dengue, Zika, chikungunya and yellow fever viruses, mosquito-59 derived symbionts are now being used to suppress mosquito populations [14] and also being 60 considered to control the spread of pathogens [15]. However, studies exploring mosquito 61 symbionts for malaria control have largely remained at the laboratory stage [16,17]. Similarly, 62 the microbiota of mosquito vectors in some geographical regions are well characterized and 63 studied compared to those from other regions. In malaria vectors for example, studies on the 64 microbiota have largely focused on Sub-Saharan African species-in particular, Anopheles 65 gambiae-and to a lesser extent on those from Southeast Asia [18]. In contrast, the microbiota 66 of Latin American malaria vectors have only recently been comprehensively characterized [7, 8, 67 19-21], with these studies describing associations between An. albimanus microbiota and 68 insecticide resistance [7,8], and the factors that shape the composition of An. darlingi, An. 69 albimanus, An. nunetzovari, An. rangeli, and An. triannulatus microbiota [19][20][21]. 70 To exploit the mosquito microbiota for malaria and malaria vector control, research must 71 successfully advance from laboratory to field settings, a transition which can be fraught with 72 challenges. For example, some malaria vectors such as An. darlingi, An. vestitipennis, and An. 73 gambiae, breed in sites that are small, temporary and often difficult to find and/or access [22][23][24][25][26], 74 making it hard to obtain sufficient immature field mosquitoes for experiments. Where larval 75 habitats are plentiful and easy to find and/or access, the subsequent rearing of field-collected 76 mosquitoes to obtain uniform characteristics can pose additional challenges [27,28]. 77 Additionally, some malaria vectors belong to species complexes whose members are 78 morphologically indistinguishable [29][30][31][32], constituting another layer of complexity that needs to 79 be considered in elucidating mosquito-microbe interactions in malaria vectors. 80 These challenges, which are common to research on mosquito ecology and control, are often 81 not reported or discussed in mosquito microbiome studies. Several failed attempts at collecting 82 and rearing sufficient immature mosquitoes from the field for our previous study on the role of 83 mosquito microbiota in insecticide resistance resulted in ultimately using either wild-caught 84 adults [7] or F1 progeny derived from field-collected adult mosquitoes [8,33]. While field-caught 85 adult mosquitoes or their F1 progeny may offer insights into mosquito-microbe interactions in 86 field scenarios, obtaining adult field-collected mosquitoes with uniform and/or controlled 87 physiological characteristics is usually not feasible. Although geographically associated 88 principal coordinate analysis (PCoA), where F1 larval internal and cuticle surface microbiota 136 clustered distinctly by maternal collection site (Fig. 2). 137 Non-pairwise Shannon diversity comparisons showed significant differences in internal 138 (p=0.009) but not cuticle surface (p=0.09) microbiota of F1 laboratory-colonized larvae from 139 different maternal collection sites, indicating that there was inter-sample variation in the diversity 140 of internal but not cuticle surface microbiota of larvae when all maternal collection sites were 141 taken into consideration. A pairwise Kruskal-Wallis comparison of Shannon diversity indices 142 showed that the inter-sample variation in diversity of larval internal microbiota held true when 143 every pair of maternal collection sites was considered except between Las Cruces 3 and 4 144 ( Non-pairwise Bray-Curtis diversity comparisons showed significant differences in cuticle surface 150 (p=0.001), but not internal microbiota (p=0.12) between adult F1 mosquitoes from different 151 maternal collection sites, suggesting a loss of location-driven heterogeneity in microbial 152 community structure in internal but not cuticle surface microbial niche of laboratory-colonized F1 153 adults. Pairwise PERMANOVA comparisons of Bray-Curtis distances also showed significant 154 differences in microbial community structure of F1 adult cuticle surface microbiota (q<0.01) 155 between every pair of maternal collection sites (Table 2a). These results were corroborated by 156 PCoA which showed that F1 adult cuticle surface microbiota, but not internal microbiota, 157 clustered distinctly by maternal collection site (Fig. 2). 158 Non-pairwise Shannon diversity comparisons showed no differences in the internal (p=0.42) or 159 cuticle surface (p=0.4) microbiota of F1 adults from different maternal collection sites, indicating 160 that there was little or no inter-sample variation in diversity of F1 adult microbiota when all 161 maternal collection sites were taken into consideration. Pairwise Kruskal-Wallis comparisons of 162 Shannon diversity indices also detected no inter-sample variation in diversity of F1 adult cuticle 163 surface or internal microbiota when every pair of maternal collection site was considered (Table  164 2b and Suppl. 1). 165 Laboratory-colonized F1 An. albimanus larvae comprised a rich and diverse microbiota 166 that differed by maternal collection site 167 Overall, ASVs from larval internal microbiota were assigned to 180 bacterial taxa, and cuticle 168 surface microbiota to 194 bacterial taxa (suppl 2.). A majority of these taxa across all locations 169 (ranging from 118-139 taxa) were shared between the internal and cuticle surface microbiota 170 (Fig 3a), as well as across maternal collection sites (n=110 for cuticle surface and n=117 for 171 internal microbiota) (Fig 3b). While a majority of the identified microbial taxa were shared 172 between both microbial niches, their abundance was generally higher in internal (Fig 4a) 173 compared to cuticle surface (Fig 4b) microbiota. Although a majority of identified microbial taxa 174 in both internal and cuticle surface microbiota were shared across all locations, their abundance 175 differed by maternal location (Fig 4a, 4b and 5). 176 In general, larval internal microbiota was dominated by ASVs identifed as an uncharacterized 177 Enterobacteriaceae, Leucobacter, Thorsellia, and Chryseobacterium (Fig 4a), together making 178 up over 50% of ASVs (Suppl. 2). In contrast, Acidovorax, unchracterized Comamonadaceae, 179 and Paucibacter (Fig 4b) made up over 50% of ASVs detected on the larval cuticle surface Unlike the internal microbial niche, no microbial taxa was predominant in larval cuticle surface 198 microbiota across all three collection sites. However, some taxa showed notable patterns of 199 abundance between locations (Fig 5). These included the genus Azoarcus, which was detected 200 at low to moderate frequencies in 13 of 15 pools of larvae from El Terrero, at low frequency in a 201 single pool of larvae from Las Cruces 3, and was not detected at all in Las Cruces 4 (Fig 4b and  202 6). Similarly, ASVs assigned to the genus Spirosoma were detected at moderate frequencies in 203 all pools of larvae from Las Cruces 4, but only in a few pools from the other two locations. ASVs 204 assigned to the genus Paucibacter were present at relatively higher abundance in larvae from 205 both Las Cruces 3 and El Terrero compared to those from Las Cruces 4. Those assigned to the 206 genus Acidovorax were predominant in larvae from Las Cruces 3 and Las Cruces 4 in contrast 207 to El Terrero. ASVs assigned to Microbacterium, Bdellovibrio and Pelomonas were present at 208 moderate frequencies in larvae from both Las Cruces 3 and Las Cruces 4 but were not detected 209 in El Terrero (Fig. 5). Bacterial taxa that were unique to each maternal collection site comprised 210 <8% of larval cuticle surface microbiota (Fig 3b), and were below the threshold for inclusion in 211 the heatmap and differential abundance testing (Suppl. 2). ASVs from adult internal microbiota were assigned to 62 microbial taxa and cuticle surface 216 microbiota were assigned to 106 microbial taxa. Two of these ASVs which were only present in 217 the cuticle surface microbiota were classified as archaea, while all other remaining ASVs were 218 classified as bacteria (Suppl. 2). Unlike larval microbiota, less than half of the assigned taxa 219 across all locations (ranging from 19-37 taxa) were shared between internal and cuticle surface 220 microbiota (Fig 3a), and only 18 taxa on the cuticle surface and 19 internal taxa were shared 221 across all maternal collection sites (Fig 3b). 222 Overall, ASVs assigned to the bacterial genus Asaia dominated both adult internal and cuticle 223 surface microbiota (Fig 6), constituting at least 70% of taxa in each microbial niche (Suppl. 2). A 224 majority of identified taxa in adult internal, but not cuticle surface, microbiota was detected 225 across all three maternal collection sites, with a few of these taxa present in high abundance 226 across all collection sites (Fig. 6). Across all three maternal collection sites, ASVs assigned to 227 the genera Acinetobacter, Gluconobacter, Pantoea and Pseudomonas were present in 228 moderate to high abundance in adult internal microbiota in addition to Asaia (Fig 6). 229 After excluding low abundance taxa (Suppl. 2), the number of remaining taxa did not meet the 230 requirements for identifying collection site-specific microbial taxa in adult cuticle surface 231 microbiota. This was compounded by dominance (>70%) of ASVs that were assigned to the 232 bacterial genus Asaia (Suppl. 2). In addition, the cuticle surface microbiota of adults originating 233 from Las Cruces 4 comprised 43% of all adult cuticle surface microbial taxa (Fig 3b), although a 234 majority were of low abundance. 235

Discussion 236
The scientific community is increasingly investigating the role of mosquito microbiota in fighting The low inter-sample variation in microbial diversity observed in this study has largely been 280 described in laboratory mosquito colonies [38,50]. The microbial composition of laboratory-281 reared larvae is typically less diverse [50, 51] compared to those of field-derived larvae, but our 282 laboratory-reared larvae exhibited a rich microbial composition that was comparable to those of 283 field populations [39,40]. In contrast, our adult progeny had a less diverse microbial composition 284 that was reflective of typical laboratory-reared adult mosquitoes [36,52]. These findings further 285 suggest that field-acquired microbiota, although transferred to laboratory progeny, may be lost 286 within one generation of laboratory colonization-particularly at the adult stage. 287 In this study, we detected microbial taxa that have previously been identified in Anopheles and 288 other mosquito genera [7, 41, 53, 54]. While a majority of the taxa in F1 larvae were shared 289 between both the internal and cuticle surface microbial niches, a greater abundance of microbial 290 taxa was detected in the internal microbial niche compared to the cuticle surface. The cuticle 291 surface microbiota of mosquitoes and other hematophagous insects are largely uncharacterized 292 and the mechanisms underlying their assemblage remain unknown. As such, we hypothesize 293 that although both internal and cuticle surface niches are exposed to the same water from which 294 the microbiota is derived, a more conducive and protected internal environment could allow for 295 greater proliferation of colonizing bacteria. In F1 adults however, less than half of the detected 296 microbial taxa were shared between the internal and cuticle surface microbial niches, suggesting 297 differences in physiological conditions that favor microbial colonization, and corroborating 298 findings that point toward a microbial regulatory mechanisms within the mosquito midgut [47][48][49]. 299 This minimal overlap of taxa between internal and cuticle surface microbial niches also suggests 300 a difference in the fate of maternally derived microbes between both niches. Although a few 301 microbial taxa overlapped between adult internal and cuticle surface microbial niches and the 302 most abundant taxa were shared, many of the unshared taxa have been previously detected in 303 adult mosquitoes including Anopheles [1, 54, 55], indicating that the cuticle surface microbiota 304 characterized in this study are inherently associated with mosquitoes. Like the larval microbiota, 305 there was a higher abundance of microbial taxa in the adult internal microbial niche compared to 306 the cuticle surface, further supporting the hypothesis of a more conducive and protected internal 307 environment permitting greater proliferation of colonizing bacteria. 308 With the exception of the adult cuticle surface microbial niche, a majority of all detected microbial 309 taxa overlapped between maternal collection sites in both F1 larvae and adults, albeit with 310 differing abundances. This reflects restrictions imposed by controlled laboratory environments in 311 the development of mosquito microbiota. In both microbial niches of both larvae and adults, 312 microbial taxa that were specific to maternal collection sites were low in abundance, compared 313 to the moderate to high abundance of those that were shared across all locations. This was 314 particularly true for Asaia-notorius for rapidly colonizing laboratory mosquitoes [56]-which 315 constituted at least 70% of both adult internal and cuticle surface microbiota from progeny 316 across all maternal collection sites. These results suggest that field-acquired mosquito 317 microbiota may be lost in as early as the first generation of laboratory colonization. 318 We recognize that not having the microbial community profiles of the mothers from which the F1 319 progeny were derived is a limitation of this study. However, these are unanticipated findings that 320 arose from a separate study whose focus was on field-derived F1 progeny reared under 321 controlled settings [8]. The findings herein provide empirical data for further exploring the role of 322 parentage and environmental conditions on the assemblage of the mosquito microbiome, and 323 the fate of field-derived microbes upon laboratory colonization. This is critical for advancing 324 mosquito microbiome studies and their applications beyond laboratory settings. 325

Methods 326
The findings presented here extend those of a larger study [8]. Thus, the mosquito collection, 327 processing and sequencing procedures have previously been described in detail [8].

Diversity indices 455
Analysis of microbial diversity within (alpha diversity) and between (beta diversity) samples were 456 performed in QIIME2 using the Shannon diversity index and Bray-Curtis dissimilarity index, 457 respectively. The Shannon diversity indices were calculated using rarefied ASVs counts per 458 sample, in which ASVs per sample were selected randomly without replacement at an even 459 depth (Suppl. 4) for ten iterations. The resulting average Shannon indices are presented and 460 were compared between samples using pairwise Kruskal-Wallis tests with Benjamini-Hochberg 461 false discovery rate (FDR) corrections for multiple comparisons. 462 The Bray-Curtis dissimilarity indices were computed with or without rarefaction, and resulting 463 indices were compared between samples using pairwise PERMANOVA tests (999 permutations) 464 with FDR corrections. There were no discernable differences between results of rarefied and 465 non-rarefied data. Thus, results of Bray-Curtis dissimilarity indices using non-rarefied data were 466 visualized by Principal Co-ordinates Analysis (PCoA) plots in R [63] using the phyloseq R 467 Significance for both pair-wise analyses was set to q <0.05 (i.e. post FDR p-value corrections). 469

Taxonomic analysis and differentially abundant microbial taxa 470
Taxonomic analysis of ASVs was performed using QIIME2's pre-trained Naïve Bayes classifier 471 to an effect size of log F≥20 and W≥20, i.e. a taxon was differentially abundant across maternal 481 collection sites if the ratio of its abundance to those of at least 20 other taxa (25% of all included 482 taxa) differed significantly across sites. 483 Only annotated ASVs with counts ≥ 2000 (larvae) or ≥ 1000 (adults) were included in the 484 heatmaps and ANCOM analysis. Prior to each analysis, ASV frequency data was normalized by 485 log10 transformation following the addition of pseudocounts of 1. 486 The outputs of data analyses were aesthetically formatted using Inkscape [69].     ADULTS variance in the data, with both internal and cuticle surface microbiota clustering distinctly by maternal collection site. For adults, the first two PC axes captured 59% (internal) and 47% (cuticle surface) of the variance in the data, with cuticle surface but not internal microbiota clustering distinctly by maternal collection site. PERMANOVA statistics are presented at the bottom of each plot.    and a cut-off of differential abundance set to W≥20 (i.e. a taxon was differentially abundant across maternal collection sites if the ratio of its abundance to those of at least 20 other taxa (25% of all included taxa) differed significantly across sites). Differentially abundant taxa are highlighted (blue shaded area) and the taxa names and locations in which they were most abundant are presented in the adjoining tables. Figure 6. Frequency of ASVs from the internal and cuticle surface microbiota of laboratory-colonized F1 adult An. albimanus originating from different locations. ASVs were annotated to the genus level or the lowest possible taxonomic level (in square brackets) and are clustered by the average nearest-neighbors chain algorithm. Only taxonomically annotated ASVs with frequencies ≥1000 are presented.  Table 2. Pairwise alpha and beta diversity comparisons of laboratory colonized F1 An. albimanus microbiota from different maternal collection sites. a. Pairwise beta (Bray-Curtis) diversity comparison showed significant differences in larval internal and cuticle surface microbiota between maternal collection sites. In contrast, only adult cuticle surface but not internal microbiota were significantly different across maternal collection sites. b. Pairwise alpha (Shannon) diversity comparison showed significant differences in larval internal but not cuticle surface microbiota between maternal collection sites (two of the three pairs). In contrast, there was no significant difference in adult internal or cuticle surface microbiota between maternal collection sites. Pairwise alpha and beta diversity comparisons were conducted using Kruskal-Wallis and PERMANOVA (999 permutations) tests respectively, with Benjamini-Hochberg FDR correction (q-value). Significance was determined at q < 0.05.