Differentiation of Synanthropic Fleas from Andalusia (Spain) through Geometric Morphometrics Analysis

Citation: García-Sánchez, A.M.; Trujillo, I.; Zurita, A.; Cutillas, C. Differentiation of Synanthropic Fleas from Andalusia (Spain) through Geometric Morphometrics Analysis. Animals 2024,14, 1582. https:// doi.org/10.3390/ani14111582 Academic Editor: Kurt Pfister Received: 3 May 2024 Revised: 20 May 2024 Accepted: 24 May 2024 Published: 27 May 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). animals Article Differentiation of Synanthropic Fleas from Andalusia (Spain) through Geometric Morphometrics Analysis Angela M. García-Sánchez , Ignacio Trujillo, Antonio Zurita * and Cristina Cutillas Department of Microbiology and Parasitology, Faculty of Pharmacy, University of Seville, Profesor García González 2, 41012 Sevilla, Spain; agar[email protected] (A.M.G.-S.); [email protected] (I.T.); [email protected] (C.C.) *Correspondence: [email protected] Simple Summary: Fleas are blood-sucking insects that are not only a nuisance but can also act as vectors for various diseases in animals and humans, including dangerous ailments such as the bubonic plague. Identifying and classifying these insects accurately is crucial for understanding how they spread and how to control them. Geometric morphometrics, a cutting-edge technique, is proving to be an invaluable tool in this regard, alongside traditional methods and molecular biology. In the present study conducted in Andalusia, Spain, this technique successfully differentiated between three populations of fleas, providing insights into their distribution, size, and characteristics. Image processing software was employed to obtain measurements, such as perimeters and areas, of the fleas under study. These findings underscore the importance of geometric morphometrics in studying and managing arthropod populations, particularly in cases where other methods fall short or are not available. Abstract: Fleas (Siphonaptera) are ectoparasitic hematophagous insects responsible for causing bites and itchy skin conditions in both humans and animals. Furthermore, they can act as vectors of different pathogens of a wide variety of diseases worldwide, including bartonellosis, rickettsiosis, and bubonic plague. Accurate identification of fleas is necessary for the study of their epidemiology, prevention, and control. In addition to traditional morphological classification approaches and molecular biology techniques, geometric morphometrics is increasingly proving to be a useful complementary tool for discriminating between Siphonaptera taxa. With the objective of determining the capacity of this technique to identify and differentiate synanthropic fleas, a principal component analysis was carried out on populations of Ctenocephalides felis,Pulex irritans, and Archaeopsylla erinacei collected in distinct regions of Andalusia (Spain). The analysis carried out on 81 male and female specimens revealed factorial maps that allowed the differentiation of the populations under study, with only partial overlaps that did not prevent their correct identification. Global size differences were also detected, with a slightly larger size in P. irritans males and a bigger size in A. erinacei females. Therefore, the present study emphasizes the role of geometric morphometrics as a useful complementary technique in taxonomic studies of arthropods, especially in the case of flea specimens lacking representative morphological features. Keywords: Siphonaptera; Ctenocephalides;Pulex;Archaeopsylla; morphometrics 1. Introduction Fleas (Siphonaptera) comprise a highly specialized order of holometabolous ectoparasitic insects with a cosmopolitan distribution and about 2700 species described so far [ 1 ]. In addition to being able to provoke bites and pruritic welts on the skin, these arthropods are also known to be vectors of different pathogens, responsible for causing a wide variety of diseases worldwide, including bartonellosis, rickettsiosis, and bubonic plague [ 2 – 9 ]. This is due to the nature of some flea species, which present a low host specificity that facilitates Animals 2024,14, 1582. https://doi.org/10.3390/ani14111582 https://www.mdpi.com/journal/animals Animals 2024,14, 1582 2 of 11 the exchanging of microorganisms, posing a potential threat to the health of both humans and animals [10–12]. The prevention and control of fleas require a large investment of money per year, which represents a significant economic burden [ 13 ]. It is crucial to enhance our knowledge about the taxonomy of fleas to develop effective strategies to reduce flea infestations and their negative impact on our environment. Recently, in addition to the traditional morphological identification and molecular biology approaches, geometric morphometrics has proven to be a useful complementary technique for discriminating taxa across different groups [ 14 – 16 ]. One of the main features of geometric morphometrics is that it is especially helpful in cases of taxa that present morphological ambiguity [ 15 ], a situation relatively common in fleas [ 17 – 19 ]. This scenario invited the exploration of the affordable criterion offered by geometric morphometrics in systematic studies on flea genera, with promising results in Ctenocephalides Stiles & Collins, 1930 [ 20 , 21 ], Ctenophthalmus Kolenati, 1856 [ 22 ], Pulex Linnaeus, 1758 [ 23 ], and Stenoponia Jordan & Rothschild, 1911 [24]. In Europe, there is evidence of an escalating frequency of vector-borne diseases and heightened pathogen circulation, primarily influenced by human-related factors [ 25 ]. One region remarkably affected by arthropod-borne diseases is Andalusia, situated in the southern of Spain, where the West Nile Virus circulation is more widespread than initially considered [26], and outbreaks have been reported in recent years [27]. Furthermore, the incidence of murine typhus, a zoonosis caused by Rickettsia typhi da Rocha Lima, 1916 transmitted to humans by fleas, seems to be increasing slowly in Andalusia [ 28 ], an aspect that reveals the ability of some flea species present in the region to transmit pathogenic bacteria. Hence, it is essential to resort to techniques that allow us to safely discern between taxa. The cat flea, Ctenocephalides felis Bouché, 1835, succeeded in its expansion as a global parasite, and it is one of the most common flea species identified in domestic dogs and cats worldwide [ 11 , 19 ]. In Southwestern Europe, C. felis is the dominant species, although, in Eastern Europe, the infestation by Ctenocephalides canis Curtis, 1826 and Pulex irritans Linnaeus, 1758 also occurs [19,29–31]. On the other hand, hedgehogs inhabit rural, urban, and suburban environments, and they are frequently parasitized by blood-sucking arthropods, such as hard ticks and fleas, including the hedgehog flea, Archaeopsylla erinacei Bouché, 1835, and other flea species such as C. felis,C. canis, and Nosopsyllus fasciatus Bosc, 1800 [ 32 – 35 ]. Since they usually cohabit with pets and humans, they can potentially act as reservoirs of pathogen microorganisms responsible for zoonoses [12]. The main objective of the present study was to determine the capacity of geometric morphometric analysis to identify and discriminate fleas from populations of C. felis, P. irritans , and A. erinacei collected in Andalusia, in order to strengthen its role as a useful complementary technique in arthropod taxonomical studies. 2. Materials and Methods 2.1. Collection of Samples Over a period of 19 months, we collected flea samples from dogs (Canis lupus familiaris Linnaeus, 1758) and one hedgehog (Erinaceus europaeus Linnaeus, 1758) that coexisted with other dogs. To gather flea samples from the hosts, we reached out to some veterinary clinics, veterinary hospitals, pet shelters, and some pet owners. In total, we contacted 145 veterinary clinics and 30 pet shelters and kennels. Among these, 18 centers agreed to participate in the sample collection (see Acknowledgements). All participants volunteered for this sampling process. Only animals parasitized by fleas were sampled. Veterinary practitioners performed an initial inspection of pets brought to their facilities. Each pet was checked for fleas and examined by a veterinarian who recorded clinical signs related to flea infestation. Adult flea counts were conducted according to the World Association for the Advancement Animals 2024,14, 1582 3 of 11 of Veterinary Parasitology guidelines [ 36 ]. In brief, the animals were combed over their entire bodies with a fine-toothed comb for 5–10 min. All captured fleas from each infested host were transferred to a plastic 1.5 mL tube containing 96% ethanol for subsequent identification and morphometrics analyses. 2.2. Morphological Identification and Metric Data Processing For morphological analysis, all specimens were initially examined under an optical microscope for specific classification. Following this, the specimens were cleared using 10% KOH, prepared, and mounted on glass slides following conventional procedures with the EUKITT mounting medium (O. Kindler GmbH & Co., Freiburg, Germany) [ 37 ]. The cleared and mounted specimens were examined again for a more detailed morphological analysis using a BX61 microscope (Olympus, Tokyo, Japan) and submitted to image capture processes with the imaging software cellSens Standard version 4.2 (Olympus, Tokyo, Japan). The diagnostic morphological characters of all samples were analyzed by comparison with figures, keys, and descriptions reported previously [ 38 – 42 ]. The measurement images of each flea were made using the image analysis software Image-PRO v11 (Media Cybernetics, Rockville, MD, USA). A total of 28 different parameters were measured for males and 36 for females (Tables 1and 2). Table 1. Biometrical data of males of C. felis,P. irritans, and A. erinacei collected from Canis lupus familiaris and Erinaceus europaeus from Andalucia (Spain). C. felis P. irritans A. erinacei MAX MIN Mean SD VC MAX MIN Mean SD VC MAX MIN Mean SD VC Global measures Area (mm2) † 1058.4 659.3 847.3 123.4 15 1379.8 688.6 1009.6 276 27 1436.7 990.3 1225.5 153.3 13 Roundness † 2.41 2.02 2.20 0.11 5 2.06 1.88 1.95 0.08 4 2.48 2.09 2.32 0.14 6 Circularity † 0.36 0.30 0.33 0.02 5 0.5 0.42 0.46 0.03 6 0.43 0.35 0.38 0.02 6 Perimeter (µm) † 5642.4 4213.9 4828.5 418.3 9 5676.4 4114.8 4925.4 649.5 13 6685.8 5424.4 5958 410.7 7 TL (µm) 2084 1563.0 1777.7 138.3 8 2027.7 1312.2 1650.0 285.8 17 2094.5 1667.3 1877.9 158.5 8 TW (µm) † 815.1 627.5 722.1 52.6 7 1064.1 772.3 926.0 120.9 13 989.4 810.1 890.0 56.4 6 Head measures Area (µm2) † 78,287 53,982 68,194 6318 9 100,673 74,318 83,921 9520 11 145,712 114,111 127,334 11,327 9 Roundness † 1.39 1.29 1.35 0.02 2 1.31 1.23 1.27 0.03 2 1.24 1.17 1.19 0.02 2 Circularity † 0.46 0.42 0.44 0.01 3 0.50 0.45 0.48 0.02 4 0.63 0.59 0.61 0.02 3 Perimeter (µm) † 1153 953.8 1072.6 49.8 5 1261.0 1071.6 1153.9 68.6 6 1502.9 1302.7 1379.8 64.0 5 HL (µm) † 391.1 306.8 360 22.9 6 357.0 293.4 317.6 25.0 8 453.2 378.3 412.6 23.2 6 HW (µm) † 251.2 210.0 228.4 12.1 5 263.0 228.3 248.2 15.1 6 378.1 323.4 352.2 16.2 5 Prothorax measures Area (µm2) † 24,848 14,287 19,192 3395 18 20,140 9635 13,081 3712 28 33,268 18,711 28,802 4038 14 Roundness † 1.45 1.23 1.37 0.06 4 2.08 1.68 1.90 0.14 7 1.60 1.25 1.43 0.11 8 Circularity † 0.58 0.46 0.51 0.04 8 0.36 0.26 0.32 0.04 11 0.61 0.38 0.46 0.07 16 Perimeter (µm) † 665.5 478.9 570.2 50.3 9 651.1 466.6 550.1 60.4 11 778.0 594.9 715.2 53.0 7 PROTW (µm) † 120.4 82.0 100.8 11.0 11 83.5 46.1 60.1 12.8 21 151.0 88.6 120.7 16.6 14 Mesothorax measures Area (µm2) † 31,142 14,043 22,358 4518 20 28,396 8581 18,186 7347 40 33,772 23,289 28,643 3716 13 Roundness † 1.64 1.33 1.46 0.08 6 2.05 1.65 1.81 0.19 10 1.92 1.40 1.72 0.19 11 Circularity † 0.57 0.42 0.48 0.04 8 0.43 0.29 0.37 0.05 15 0.55 0.37 0.42 0.05 13 Perimeter (µm) † 723.9 512.8 634.1 63.3 10 764.6 467.7 624.0 107.4 17 858.8 670.8 783.0 64.7 8 MESOW (µm) † 137.4 88.7 109.0 13.8 13 103.5 47.7 76.2 21.8 29 137.0 99.3 111.3 13.6 12 Metathorax measures Area (µm2) † 37,152 20,305 28,528 5061 18 53,522 20,280 35,569 12,210 34 48,486 33,659 38,673 4209 11 Roundness † 1.57 1.28 1.46 0.07 5 1.64 1.38 1.53 0.10 7 1.81 1.47 1.60 0.10 7 Circularity † 0.57 0.39 0.44 0.04 10 0.47 0.42 0.44 0.02 5 0.42 0.34 0.39 0.02 6 Perimeter (µm) † 877.8 625.5 758.6 71.6 9 1024.4 667.7 857.8 123.5 14 1023.2 883.7 922.7 41.9 5 METW (µm) † 142.8 102.3 120.4 12.6 10 177.1 97.5 131.4 30.4 23 157.1 109.7 134.2 13.9 10 AW (µm) † 34.9 12.9 20.7 6.0 29 51.3 19.2 37.0 12.2 33 31.3 11.3 23.1 6.2 27 TL = total length, TW = total width, HL = total length of the head, HW = total width of the head, PROTW = total width of the prothorax, MESOW = total width of the mesothorax, METW = total width of the metathorax, AW: apex width, MAX = maximum, MIN = minimum, SD = standard deviation, Mean = arithmetic mean, VC = coefficient of variation (percentage converted), † = significant differences between groups (p< 0.005). Animals 2024,14, 1582 4 of 11 Table 2. Biometrical data of females of C. felis,P. irritans, and A. erinacei collected from Canis lupus familiaris and Erinaceus europaeus from Andalucia (Spain). C. felis P. irritans A. erinacei MAX MIN Mean SD VC MAX MIN Mean SD VC MAX MIN Mean SD VC Global measures Area (mm2)2290.4 827.8 1724.7 438.2 25 2876.6 1180.3 1596.4 567.1 36 2874.6 1368.8 2023.6 434.1 21 Roundness † 2.57 1.82 2.10 0.20 10 2.11 1.80 1.90 0.08 4 2.34 1.76 2.02 0.17 8 Circularity † 0.40 0.33 0.36 0.02 5 0.50 0.40 0.46 0.02 5 0.49 0.36 0.41 0.03 8 Perimeter (µm) † 7967.9 4583.8 6661.7 837.0 13 8379.8 5310.4 6092.9 993.7 16 8733.5 6038.3 7127.7 902.6 13 TL (mm) † 2859.5 1616.2 2439.8 337.8 14 2861.0 1757.8 2041.3 372.8 18 2938.3 1885.7 2425.1 332.8 14 TW (mm) † 1208.6 767.4 1038.7 136.2 13 1495.9 1003.5 1150.2 144.0 13 1487.5 1058.3 1220.5 112.7 9 Head measures Area (µm2) † 100,169 67,749 83,173 9264 11 135,023 87,601 111,137 12,669 11 163,067 107,663 135,800 18,243 13 Roundness † 1.55 1.35 1.45 0.05 3 1.40 1.22 1.30 0.06 4 1.26 1.16 1.20 0.02 2 Circularity † 0.46 0.38 0.42 0.02 5 0.50 0.43 0.46 0.02 5 0.58 0.51 0.55 0.02 4 Perimeter (µm) † 1354.0 1102.8 1229.3 73.2 6 1455.0 1238.6 1342.4 65.3 5 1564.9 1273.1 1423.1 89.7 6 HL (µm) † 449.5 357.9 406.6 27.3 7 428.5 344.0 371.5 24.4 7 463.8 380.5 421.3 26.4 6 HW (µm) † 296.8 243.2 265.4 15.1 6 330.1 243.7 287.6 22.2 8 383.9 274.2 324.7 30.5 9 Prothorax measures Area (µm2) † 36,972 15,844 25,774 5347 21 29,118 16,764 22,842 3602 16 48,287 25,729 37,136 7542 20 Roundness † 1.92 1.40 1.65 0.14 8 2.22 1.53 1.78 0.18 10 1.50 1.26 1.42 0.08 5 Circularity † 0.53 0.36 0.45 0.05 10 0.43 0.26 0.34 0.04 13 0.59 0.41 0.48 0.05 11 Perimeter (µm) † 876.7 576.8 723.8 74.3 10 812.5 615.0 709.3 51.4 7 879.0 691.0 805.6 71.8 9 PROTW (µm) † 139.0 67.7 105.0 18.3 17 98.6 56.9 84.8 12.2 14 168.1 106.3 138.2 20.2 15 Mesothorax measures Area (µm2)48,419 20,032 35,002 8398 24 49,243 27,112 37,914 5734 15 50,800 29,397 40,732 6543 16 Roundness † 1.69 1.24 1.51 0.11 7 1.86 1.52 1.64 0.10 6 1.86 1.50 1.60 0.12 7 Circularity † 0.60 0.33 0.46 0.06 13 0.46 0.35 0.42 0.03 7 0.51 0.40 0.47 0.03 6 Perimeter (µm) † 967.0 638.1 807.6 101.4 13 1031.0 732.8 879.5 78.2 9 1012.9 783.6 899.3 75.2 8 MESOW (µm) † 161.4 88.1 135.2 19.0 14 145.5 105.9 124.5 10.0 8 168.1 113.8 140.8 15.6 11 Metathorax measures Area (µm2) † 63,421 26,207 46,240 10,448 23 73,621 48,603 63,117 7854 12 66,054 44,555 54,053 7425 14 Roundness † 2.09 1.41 1.68 0.17 10 1.73 1.37 1.51 0.10 7 1.59 1.31 1.48 0.07 5 Circularity † 0.48 0.34 0.41 0.03 9 0.48 0.37 0.44 0.03 8 0.50 0.40 0.44 0.03 7 Perimeter (µm) † 1185.4 772.5 979.9 128.9 13 1199.2 943.2 1090.1 70.3 6 1116.9 897.5 997.9 73.2 7 METW (µm) † 175.8 109.0 147.5 18.5 13 206.9 145.3 178.4 15.8 9 188.3 144.9 170.2 16.1 9 Spermatheca measures Area (µm2) † 3088 2162 2619 259 10 3489 2439 3062 309 10 11,768 3875 7474 2120 28 Roundness † 1.21 1.05 1.14 0.04 4 1.06 1.01 1.03 0.01 1 1.25 1.05 1.12 0.06 6 Circularity † 0.76 0.59 0.65 0.05 7 0.89 0.76 0.85 0.04 5 0.81 0.53 0.66 0.08 12 BULGAP (µm) † 212.1 167.8 192.7 10.9 6 210.8 176.3 198.0 10.3 5 396.7 227.0 320.4 45.6 14 BULGAL (µm) † 71.5 52.6 61.2 5.0 8 70.6 54.3 63.9 4.7 7 127.0 80.3 99.7 15.0 15 BULGAW (µm) † 58.2 46.4 50.9 3.0 6 66.7 55.6 59.6 3.1 5 133.7 57.8 90.8 22.6 25 APEHILL (µm) † 52.8 22.9 35.6 9.1 25 64.2 26.9 46.9 12.2 26 118.9 38.4 83.4 21.0 25 APEHILW (µm) † 31.7 17.0 24.7 4.4 18 64.5 23.4 31.7 10.7 34 57.9 20.9 38.1 9.4 25 DBMV (µm) † 349 131 251 57.1 23 485 290 378 56.7 15 503.8 150.3 293.4 116.5 40 TL = total length, TW = total width, HL = total length of the head, HW = total width of the head, PROTW = total width of the prothorax, MESOW = total width of the mesothorax, METW = total width of the metathorax, BULGAP: perimeter of the bulga, BULGAL: total length of the bulga, BULGAW: total width of the bulga, APEHILL: total length of the apex of the hilla, APEHILW: total width of the apex of the hilla, DBMV = distance from bulga to the ventral margin of the body, MAX = maximum, MIN = minimum, SD = standard deviation, Mean = arithmetic mean, VC = coefficient of variation (percentage converted), † = significant differences between groups (p< 0.005). Descriptive univariate statistics based on arithmetic mean, standard deviation, and coefficient of variation for all parameters were determined for male and female populations. The data were subjected to one-way ANOVA (analysis of variance) for statistical analysis of the parameters. The results were statistically significant when p< 0.05. Statistical analysis was performed using Microsoft Excel for Microsoft 365 MSO (v2402). In addition, biometric characters of fleas were compared between different species and the most significant parameters were assayed for a morphometrics study. Morphological variation was quantified using geometric morphometrics [ 43 ], a technique that provides an estimate of size integrating different growth axes into a single variable known as “centroid size” [ 44 ]. The estimate of size was represented by a single variable that reflected variation in multiple directions, as many as there were landmarks under study, and shape was defined as their relative positions after correction for size, position, and orientation. With these informative data, and the corresponding software Animals 2024,14, 1582 5 of 11 freely available to conduct complex analyses, significant biological and epidemiological features can be quantified more accurately [45]. Multivariate analyses were applied to assess phenotypic variations among the samples, using size-free canonical discriminant analysis on the covariance of log-transformed measurements. These analyses are applied to exclude the effect of within-group ontogenetic variations by reducing the effect of each character on the first pooled within-group principal component (a multivariate size estimator) [ 46 ]. principal component analysis (PCA) was used to summarize most of the variations in a multivariate dataset in a few dimensions [ 47 ]. Morphometric data were explored using multivariate analysis in three parameters in males (TW, HW, and AW) (Table 1) and females (Global Circularity, BULGAP, and HL) in females (Table 2) using BAC v.2 software [21,48]. 3. Results A total of 81 fleas (34 males and 47 females) were collected from different regions of Andalusia and classified as follows: 39 as C. felis (18 males and 21 females), 19 as P. irritans (6 males and 13 females), and 23 as A. erinacei (10 males and 13 females) (Table 3). All C. felis specimens and three P. irritans (the only male from Huelva and two female fleas from Seville) were collected from dogs (Canis lupus familiaris), whereas A. erinacei were collected from a hedgehog host. The rest of the P. irritans fleas were collected off-host from a neglected horse stable (Table 3). Table 3. Distribution of fleas collected from dogs from different geographical origins. Geographical Origin C. felis (Number of Fleas) P. irritans (Number of Fleas) A. erinaceid (Number of Fleas) Male Female Male Female Male Female Sanlúcar de Barrameda (Cadiz, Spain) 18 21 - - - - Seville (Seville, Spain) - - 5 13 - - Huelva (Huelva, Spain) - - 1 - - - Dos Hermanas (Seville, Spain) - - - - 10 13 Total 18 21 6 13 10 13 To carry out the classification of the samples, we considered descriptions used traditionally to discern between these species and, additionally, remarkable morphological features based on the measurements performed. Statistical tests showed several significant measurements for subsequent morphometric analyses. Therefore, the following parameters were used: total width (TW), total width of the head (HW), and apex width (AW) in males (Table 1) and total length of the head (HL), perimeter of the bulga (BULGAP), and Global Circularity in females (Table 2). This perimeter is the length of the bulga’s boundary, whereas the circularity is calculated as the ratio of the area of an object against a circle whose diameter is equal to the object’s maximum feret. The influence of size was analyzed using PCA in C. felis,P. irritans, and A. erinacei, involving the regression of each character separately on the within-group first principal component (PC1). The resulting factor maps for male and female populations are shown in Figures 1and 2, respectively. Male variables significantly correlated with PC1, contributing 71% to the overall variation. The male factor maps showed global size differences in the flea populations, with a slightly larger size in P. irritans males (Figure 1). The three male communities are well grouped in the factor map, with a lack of noteworthy overlapping areas between them. Only C. felis and P. irritans showed a partial overlap but with no inconvenience in their identification. On the other hand, female variables significantly correlated with PC1, contributing 90% to the overall variation. The resulting factor maps (Figure 2) clearly illustrate global size differences in the populations analyzed, including a bigger size in A. erinacei. As in the previous factor maps, there is a lack of notable overlapping areas between the female populations. As in the male factor maps, C. felis and P. irritans showed a partial overlap that did not prevent their identification. Animals 2024,14, 1582 6 of 11 Animals 2024, 14, x FOR PEER REVIEW 7 of 12 Figure 1. Factor map corresponding to C. felis, P. irritans, and A. erinacei male adults. Samples are projected onto the first and second principal components: PC1 (71%) and PC2 (26%). Each group is represented by its perimeter. Figure 2. Factor map corresponding to C. felis, P. irritans, and A. erinacei female adults. Samples are projected onto the first and second principal components: PC1 (90%) and PC2 (8%). Each group is represented by its perimeter. On the other hand, female variables significantly correlated with PC1, contributing 90% to the overall variation. The resulting factor maps (Figure 2) clearly illustrate global size differences in the populations analyzed, including a bigger size in A. erinacei. As in the previous factor maps, there is a lack of notable overlapping areas between the female Figure 1. Factor map corresponding to C. felis,P. irritans, and A. erinacei male adults. Samples are projected onto the first and second principal components: PC1 (71%) and PC2 (26%). Each group is represented by its perimeter. Animals 2024, 14, x FOR PEER REVIEW 7 of 12 Figure 1. Factor map corresponding to C. felis, P. irritans, and A. erinacei male adults. Samples are projected onto the first and second principal components: PC1 (71%) and PC2 (26%). Each group is represented by its perimeter. Figure 2. Factor map corresponding to C. felis, P. irritans, and A. erinacei female adults. Samples are projected onto the first and second principal components: PC1 (90%) and PC2 (8%). Each group is represented by its perimeter. On the other hand, female variables significantly correlated with PC1, contributing 90% to the overall variation. The resulting factor maps (Figure 2) clearly illustrate global size differences in the populations analyzed, including a bigger size in A. erinacei. As in the previous factor maps, there is a lack of notable overlapping areas between the female Figure 2. Factor map corresponding to C. felis,P. irritans, and A. erinacei female adults. Samples are projected onto the first and second principal components: PC1 (90%) and PC2 (8%). Each group is represented by its perimeter. 4. Discussion The accurate classification of fleas requires careful morphological examination or molecular confirmation, and therefore, the possibility that prior studies may have inadvertently misidentified fleas cannot be discarded [ 19 , 49 ]. In fact, authors like Ménier and Beaucournu reported numerous misidentifications in specimens of the genus Cteno- Animals 2024,14, 1582 7 of 11 cephalides [ 50 ]. The study of flea epidemiology, control, and prevention requires the accurate identification of species and subspecies. In general, the classification of genera and species of fleas is based on external morphological characters. The presence or absence of combs and eyes, along with the length of the head, are typically significant features in morphological identification [ 51 ]. However, the size itself could never represent a way to reliably recognize the sex or the species of a flea specimen [ 52 ], and some flea species do not have easily identifiable morphological characters. For instance, A. erinacei and P. irritans do not possess pronotal or genal combs, so their classification process can be more complex in case the required specialized skills in flea identification are lacking. It is necessary to pay great attention to detail to recognize developmental stages and adequate sex identification [ 52 ]. Additionally, C. felis is a good example of a flea species known for its morphological ambiguity and the underlying issues in the study of their global populations [ 19 ]. In terms of molecular biology techniques, the notable lack of large-scale phylogenetic data for flea taxa causes some genera like Ctenocephalides to not have a defined genetic identity [ 17 , 19 , 40 ], especially if we consider subspecies [19]. Furthermore, it is still surprising that, despite the considerable veterinary and public health significance of dog fleas, studies investigating the diversity of these ectoparasite species on pets and the occurrence of flea-borne pathogens are scarce in certain regions [ 20 ]. Given the difficulties associated with flea morphological identification, the limited genetic information available, and the insufficient knowledge of the common pathogens of each flea species, the need to resort to complementary diagnosis techniques arises. Geometric morphometrics analysis is one of these novel approaches applied to parasitological diagnosis, usually employed in arthropod identification [ 43 ]. The technique is based on the utilization of computer software for data processing and interpretation, with the advantage being that costly reagents and equipment are not required. Its affordability and the simplicity of data collection make it especially useful in low-resource settings [52,53]. To the best of our knowledge, the present work is the first in which flea measurements have been obtained using the imaging software Image-PRO. This program has been used before to study arthropods and other parasites [ 54 – 57 ]. It allowed us to incorporate into the analysis accurate measures such as areas, perimeters and circularities of the flea specimens for the first time. Global Circularity and BULGAP were revealed as useful features that contribute to the identification of flea species via geometric morphometrics. The distribution of the three analyzed flea species showed a comparable pattern in both factor maps. A. erinacei appeared distant from C. felis and P. irritans, showing an appreciably larger size in the case of females. C. felis and P. irritans presented a small overlapping area, which did not prevent their individual identification. In both cases, P. irritans has always appeared larger than C. felis. Although A. erinacei and C. felis are part of the Pulicinae family, the factor maps illustrated that fleas at the same taxonomic level are not necessarily closer at the morphological level since A. erinacei appears further away from both C. felis and P. irritans. The selection of representative measurements for the morphometrics analyses was in accordance with previously published works. Total width (TW), head width (HW), and apex width (AW) are consolidated as useful parameters that define the morphological identity in males [ 21 , 50 , 58 ], as well as the total length of the head (HL) and the perimeter of the bulga (BULGAP) for females [ 21 ]. Due to the lack of genal ctenidium in P. irritans and A. erinacei, the difference in length between first and second spines (DEG parameter [ 21 ]) could not be considered in the present analysis, whereas the inclusion of the degree of elongation of the apical part (hilla) in females offered similar results but with a bit more overlap between P. irritans and C. felis. This is why the parameter APEHILL [ 21 ] was substituted by BULGAP, which permits the best differentiation between species. The three analyzed flea species are among the most frequent in our environment, and, as a result, there is a notable risk of encountering them, with consequently associated Animals 2024,14, 1582 8 of 11 parasitism suffered by humans and animals. After applying geometric morphometrics to differentiate flea communities of the same genera [ 21 – 24 ], the present work represents a step further, since this technique allowed us to identify different flea genera. 5. Conclusions Accurate identification of fleas is necessary for studying the epidemiology, prevention, and control of these arthropods. In situations of uncertainty, alternative approaches are required to ensure correct classification. Geometric morphometrics is increasingly recognized as a reliable complementary technique for identifying flea species, particularly valuable in environments with limited resources. In the present work, we were able to discern between the flea species A. erinacei, P. irritans, and C. felis using principal component analysis of males and females. Differences in overall size were also detected: A. erinacei presented the largest size in females, whereas P. irritans was slightly larger in males. Therefore, morphometrics is a relevant technique with great potential for application in the field of fleas, considering the existence of species that have traditionally posed challenges in their identification. Author Contributions: Conceptualization, C.C. and A.Z.; methodology, A.M.G.-S.; software, A.M.G.- S. and I.T.; validation, A.Z. and C.C.; formal analysis, C.C.; investigation, A.M.G.-S. and I.T.; resources, C.C.; data curation, A.M.G.-S.; writing—original draft preparation, A.M.G.-S.; writing—review and editing, A.Z. and C.C.; visualization, C.C.; supervision, A.Z. and C.C.; project administration, C.C.; funding acquisition, C.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by a project from the Junta de Andalucía, European Regional Development Fund (FEDER) (Ref. P20_00544). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are available in the article. Acknowledgments: We would like to express our gratitude to these participating veterinary clinics, pet shelters, and kennels for their continued support and timely submission of samples, which greatly contributed to the success of our study. Veterinary clinics: El acuario, Ayamonte, Huelva; Animal-Vetx El Saladillo, Huelva; Cuenca minera, Minas de Río Tinto, Huelva; Consultorio veterinario Galaroza, Galaroza, Huelva; Roncal, Pilas, Sevilla; Mascotasalud, Tomares, Sevilla; Ronda de capuchinos, Sevilla; Vilovet, Cazalla de la Sierra, Sevilla; Taxana, Los Rosales, Sevilla; Sobrino E Illescas, Ecija, Sevilla; SyR, Estepa, Sevilla; Alfavet, Fuente Palmeras, Córdoba; Mascovet, Posadas, Córdoba; El Pinar, Puerto de Santa María, Cádiz; El Parque, San Fernando, Cádiz. Pet shelters and kennels: Mascotomares, Tomares, Sevilla; Arca, Sevilla; Sociedad protectora de animales y plantas, Sevilla. Conflicts of Interest: The authors declare no conflicts of interest. References 1. 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