The variations of five Colletotrichum strains from strawberry in mycelial growth and pathogenicity below 26℃

doi:10.21203/rs.3.rs-3982707/v1

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The variations of five Colletotrichum strains from strawberry in mycelial growth and pathogenicity below 26℃

https://doi.org/10.21203/rs.3.rs-3982707/v1

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Anthracnose caused by Colletotrichum spp. is a serious threat to many crops. C. siamense has been increasingly prevalent recently. However, the biology and pathogenicity of these fungi was largely elusive, especially below 26°C. Currently, the mycelial growth of five representative Colletotrichum strains including three C. siamense, one C. fructicola and one C. gloeosporioides s.s. strain from diseased strawberry was characterized at 10, 14, 18, 22 and 26℃. Their pathogenicity to two hosts under 14℃ and 22℃ was investigated. These strains did not differ much in mycelium growth between 10–26℃, although all C. siamense and C. gloeosporioides s.s. strains showed some superiority than C. fructicola. However, great variations were observed in their pathogenicity to Fragaria vesca and F. × ananassa cv. ‘Benihoppe’. The strain Cs:GQHZJ19 with fastest mycelial growth at 22℃ was also the most virulent to both hosts under 14 / 22℃. But the mycelial growth rate was only positively correlated with C. siamense pathogenicity to the susceptible cv. ‘Benihoppe’ at 3 dpi under 22℃. Based on the pathogenicity analysis for five Colletotrichum strains on hosts with varying susceptibility under distinct temperatures, this work suggested that host genotype might play a decisive role in disease severity from the beginning of infection, while temperature could shape host-Colletotrichum spp. interaction at a later infection stage. Future studies with more fungal samples are required to determine the biology and virulence of Colletotrichum strains (especially C. siamense) in a wider temperature range, which will eventually facilitate an effective management of crop anthracnose.

Colletotrichum spp.

temperature

mycelial growth

pathogenicity

strawberry

Strawberry is a nutritious and popular small fruit crop all over the world. It belongs to the genus Fragaria in the family Rosaceae, and there are four basic reproductive groups in the genus Fragaria, mainly varying with ploidy level or chromosome number (Hancock 1999). Fragaria vesca L., a diploid (2n = 2x = 14) strawberry, is a relative of the commercial octoploid strawberry, also the predominant sub-genome provider for octoploid strawberry (Oosumi et al. 2006; Edger et al. 2019). The octoploid strawberry F.× ananassa Duchesne (2n = 8x = 56) is the major cultivated group (Davis et al. 2007). Rosaceae is reported to be the family with the highest number of records associated with the filamentous fungal Colletotrichum genus, with as many as 41 Colletotrichum species being pathogenic to rosaceous plants (Talhinhas & Baroncelli 2021). Indeed, strawberry is susceptible to a wide range of phytopathogenic organisms and is considered as a model system for Rosaceae family (Amil-Ruiz et al. 2011).

As one of the oldest fungi on Earth co-evolved with flowering plants, the genus Colletotrichum consists of more than 280 species of Ascomycota, consisting of 16 species complexes and 15 additional singletons (Liu et al. 2022). Colletotrichum is a very dominant plant pathogen that causes anthracnose leaf blight or fruit/stem rot on more than 3,000 species of plants (O’Connell et al. 2012). Anthracnose, caused by Colletotrichum spp., is a serious threat to strawberry industry, as anthracnose can infect a wide range of strawberry tissues, causing black spots on leaves, petioles, stolons, and fruits that are sunken or necrotic, leading to wilting of the entire plant due to crown rot (Howard et al. 1992). C. siamense and C. fructicola of C. gloeosporioides sensu lato are currently the most prevailing species infecting strawberries in Asia (Ji et al. 2022), which was closely related with their broad host range, vital environmental adaptation and powerful genetic flexibility (da Silva et al. 2020; Wilson et al. 2019).

Temperature is one of the key environmental factors affecting pathogen survival and aggressiveness (Velásquez et al. 2018). Epidemics caused by Colletotrichum spp. generally occur in a wet and warm weather, at temperatures between 20 ℃ and 30 ℃ (Ngugi et al. 2000; Sharma and Kulshrestha 2015; Soares-Colletti and Lourenço 2014). The temperature requirements of Colletotrichum fungi vary with the biological process, fungal genotype and ecotype (Chung et al. 2020; Moreira et al. 2021; Soares-Colletti and Lourenço 2014). The optimal temperatures for mycelial growth of Colletotrichum spp. largely range from 24℃ to 28 ℃ (Salotti et al. 2022). The favorable temperature for mycelial growth was proposed between 25.83℃ to 28.22℃ for several representative Colletotrichum strains from eastern China (Ji et al. 2023). C. siamense has been one of the most predominant species threatening strawberry worldwide with an advantageous tolerance to higher temperature especially in mycelial growth (Ji et al. 2022, 2023). Previous studies have described the morphological characteristics and the pathogenicity of different Colletotrichum species under high temperatures (Damm et al. 2014; Dubrulle et al. 2020; He et al. 2019; Ji et al. 2023; Munir et al. 2016; Weir et al. 2012). However, the biology and pathogenicity of Colletotrichum species especially the prevailing C. siamense under low-temperature conditions has not been studied yet. To bridge the gaps in the temperature requirements of the prevailing Colletotrichum species, thermal phenotyping was necessary under a low-temperature range. Such investigation would contribute to the risk assessment and management of Colletotrichum spp. in a wide range of temperatures.

The long-term goal of our lab is to provide useful information for the management of anthracnose. Our previous work (Ji et al. 2023) stimulated several questions. Does the strains of C. siamense with growth superiority above 30℃ have a relatively lower risk for crop below 26℃? Does the growth rate of Colletotrichum spp. correlate with their pathogenicity to strawberry under a lower temperature range? Again, we questioned the potential tradeoff between the tolerance to high temperature among C. siamense strains and their virulence to susceptible hosts as previously suggested (Chen et al. 2017; Ji et al. 2023). The specific objective of this study using five representative Colletotrichum strains was: i) to evaluate the potential risk of Colletotrichum spp. below 26℃ via modeling mycelial growth and pathogenicity analysis, ii) to examine the possible tradeoff between temperature adaption and fungal pathogenicity and iii) to compare the relative influence of temperature and host genotype on strawberry disease severity upon Colletotrichum infection.

Plant materials and growth conditions

The woodland strawberry ‘Ruegen’ (F. vesca) and commercial octoploid strawberry ‘Benihoppe’ (F. × ananassa Duch) were cultivated in a strawberry greenhouse at Institute of Forestry and Fruit Tree Research, Shanghai Academy of Agricultural Sciences in current work. Stolon-derived ‘Benihoppe’ and seed-germinated ‘Ruegen’ seedlings were grown under 24 ± 2 ℃ with a 14-h-light/10-h-dark rhythm. Plants were regularly watered twice a week. Fertilizer (0.1%) containing N-P-K: 15-15-15 (YaraMila, Norway) was used every one week. Old leaves were removed followed by spraying fungicides. Fungicides and fertilizer were no longer applied from two weeks prior to inoculation. The third and fourth leaves were freshly detached and used for site-specific fungal inoculation or mock treatment.

Fungal strains

Three strains of C. siamense GQHAH2, Nj-2 and GQHZJ19 with varied virulence isolated from strawberry gardens in Anhui, Jiangsu and Zhejiang Provinces of eastern China (Han et al. 2016; Zhang et al. 2020), respectively, were selected for current research. An additional strain belonged to C. gloeosporioides sensu stricto (s.s). JSH-7-1 isolated from diseased strawberry in Hubei (Han et al. 2016). One strain of C. fructicola with strong virulence maintained in current lab, was isolated from diseased strawberry in Shanghai (Ren et al. 2008) and later deposited under accession no. as CGMCC3.17371 (Zhang et al. 2016).

All five strains of three species belong to the C. gloeosporioides complex. These fungi were rejuvenated in 2022 via isolating single spore colonies from the infected leaf tissues of strawberry cv. ‘Benihoppe’. Before testing under varying temperatures, each strain was propagated on PDA plates for 7 days at 28°C in darkness.

Characterizing the growth of mycelium

The 7-day-old culture of each strain was scribed at the advancing edges with a sterilized scalpel and three mycelial pieces in a size of 1–2 mm² were transferred to a new plate (Φ = 90 mm) with fresh PDA media. For each temperature × strain combination, four replicate plates were set, each with three 1–2 mm² fresh marginal mycelia. A total of 20 plates per temperature were placed according to a completely randomized block design in a low-temperature incubator (KT053, Binder, Germany). The culture conditions were in the darkness under 10, 14, 18, 22 or 26°C.

After 3 d incubation under each temperature, both sides of the colonies were photographed. Simultaneously, the morphological characteristics including the texture, density, color, and the shape of the mycelial colonies were visually recorded. Furthermore, colony diameter was measured using ImageJ software (Rueden et al. 2017). A total of 12 data per strain per temperature were obtained for modeling and statistical analysis. The rate of mycelial extension was calculated as the average growth in 3d culture (mm/day). The experiment was independently repeated in 2022 and 2023.

Preparation of inoculum

About 10 mycelial squares in sizes of about 1cm×1cm were cut from the advancing edges of the fresh 7-d-old plates incubated under 14 or 22℃. These squares were transferred to a 250 ml conical flask with 100 ml PDB media. Conidia were produced in a shaker at 200 rpm for 4–7 days under 14℃ or 22℃, the same temperature as for mycelial culture. Then, the liquid culture collection was filtered through two-layered lens wiping tissues, quantified with a hemocytometer under Nikon Eclipse E200 microscope. Later, the solution was adjusted to 2×10⁶ conidia per ml either by dilution with distilled water or enrichment via centrifugation. Under 22℃, the conidia inoculum of all strains except for Cs: Nj2 was adjusted via dilution. By contrast, the conidia inoculum was prepared via centrifugation enrichment under 14℃ for all Colletotrichum strains.

Pathogenicity assay

The pathogenicity of Colletotrichum strains has been studied by inoculating wounded leaves, largely following the method as previously reported (Ji et al. 2023). The six treatments consisted of five fungal strains and one mock treatment (sterile water containing 0.01% (v/v) Tween-20). Each strain was inoculated on two sites of the left side on 15 leaflets as well as the low right of 12 additional leaflets per temperature × strawberry variety combination, including the third and fourth leaflets of at least eight plants. Each leaflet was inoculated with two 10µl drops (2×10⁶ per ml) of one conidial suspension on the left side, while 10 µl of mock solution and 10 µl of mock or an additional conidial suspension were inoculated on the upper right and low right, respectively. A total of 42 inoculation sites were studied per strain × temperature × strawberry variety.

After inoculation, petri dishes with leaflets were incubated in a dark incubator at 14 or 22°C (the same temperature for mycelial culture and conidia production) for 48h, followed by a 14h/10h light/dark cycle. Plant materials were photographed and recorded at 3 days or 5 days post inoculation (dpi). After the lesion size was calculated using ImageJ software, disease grading and disease index (%) were determined following rules described previously (Ji et al. 2014; Zhang et al. 2020). Experiment was carried out twice in 2023 independently.

Model fitting and statistical analysis

To reveal the distinct responses of Colletotrichum strains to temperatures (10–26℃) in mycelium growth, two-way ANOVA (Tukey-test, P ≤ 0.001) was performed. Mycelium growth rate was compared between fungal strains by Duncan’s two factor test (P ≤ 0.05). A polynomial model was used to establish a response curve for the growth rate of Colletotrichum mycelium at different temperatures. The mycelial growth rate of each strain at different temperatures was analyzed using linear regression analysis in Statistical Product and Service Solutions (SPSS), modelled with a quadratic function, and written as:

Y (T) = b0 + b1*T^1 + b2*T^2 (1)

where T is the independent variable temperature, Y is the dependent variable mycelium growth rate, and three parameters of the model include b0 the intercept, b1 and b2 the coefficients of T and T-squared.

In addition, a linear regression analysis was performed to evaluate the relative influence of ‘temperature’ and ‘host genotype’ on the disease severity caused by Colletotrichum pathogen in strawberry, which was modelled with a linear function and written as:

Y = a*X + b (2)

where Y is disease index as the dependent variable, X is temperature or host genotype as independent variables, a is the coefficients for certain independent variable (slope) and b is the constant of the equation (intercept).

Parametric correlation evaluation between ‘mycelium growth rate’ (under 14/22℃) and Colletotrichum pathogenicity (‘disease index’) (in F. vesca / F. × ananassa), and nonparametric correlation for ‘temperature’, ‘host genotype’ and ‘fungal ecotype’ with ‘disease severity’ were performed using the CORREL analysis in SPSS. The SPSS 25.0 statistics was used for the regression and statistical analysis.

Mycelium morphology of strawberry-pathogenic Colletotrichum strains under 10°C − 26°C

Five representative Colletotrichum strains from eastern China were selected for mycelium characterization after 3d-incubation in darkness on PDA at 10 to 26°C (Fig. 1). Differences in the colony morphology of these five strains could be observed under all temperatures tested except for 10°C, although the mycelial growth trend of the five fungi did not differ much. After three days’ incubation under 14°C, Cs:GQHZJ19 developed relatively denser mycelia while Cf: CGMCC3.17371 formed thinner mycelia than the rest fungal strains.

Under 18–26°C, C. siamense and C. gloeosporioides s.s. were largely greyish-white with abundant mycelium, intact margin, and a pale orange dorsal surface. At 18°C, the plates of all five strains were greyish-white with markedly elevated centers, although their reverse sides uniformly displayed an orange center except for Cf: CGMCC3.17371. Under 22°C, C. siamense GQHZJ19 produced white dense mycelium with a gradually declining outside edge together with brown conidial mounds forming in the center, which was much clear than that at 18°C and 26°C. Generally, Cs:Nj2 looked like Cf: CGMCC3.17371 under 22–26°C, although a relatively faster growth was observed in the former. In fact, the colonies of C. fructicola at 18–26 ℃ were greyish white, actively growing, with relatively sparse and fluffy edges, and the mycelium was visible on the back of all plates in a clockwise spinning growth. There was no discernible difference between the colonies under the conditions of 22℃ and 26℃.

Morphologically, C. gloeosporioides s.s. JSH-7-1 was basically the same as C. siamense GQHAH2 under 18–26℃, but the mycelium of Cg:JSH-7-1 was more abundant and compact than Cs:GQHAH2.

The above observations were largely coincident with a previous work (Ji et al. 2023), although clear differences were observed for Cs: GQHZJ19 and Cf: CGMCC3.17371. In that work, Cs:GQHZJ19 colony was markedly raised in the center under 22℃ and 26℃, which was not observed in current work. For C. fructicola, olivaceous gray flocculent in the center was observed in our previous work but not in current work. Fungal morphology is easily affected by cultivation, and these minor differences might be interpreted from distinct incubation duration, different starting materials or unknown factors.

Mycelial growth rates of Colletotrichum strains under different temperatures

The average mycelial growth rates of each strain were quantified from 10 to 26℃ (Fig. 2). Significant differences among Colletotrichum strains were detected under all temperatures tested. At 10℃, the mycelial growth rate of Cf: CGMCC3.17371 was slower than that of Cs:Nj2 (Fig. 2a). Indeed, the mycelia of Cf: CGMCC3.17371 grew at the lowest rate under all temperatures in this study. Generally, the rest strains grew at similar rates without significant differences. However, the mycelial growth rates of Cs:GQHAH2, Cg:JSH-7-1 and Cs:GQHZJ19 peaked at 14℃, 18℃ and 22℃, respectively. Morphologically similar, Cg:JSH-7-1 and Cs:GQHAH2 grew at similar speed under 22–26℃, while their growth rates were significantly different from each other under 14 and 18℃. Another pair Cf: CGMCC3.17371 and Cs:Nj2 grew at significantly distinct rates under all temperatures except for 22℃ (11.89 and 12.38 mm/d). The growth rate of Cs:GQHZJ19 ranked under 22°C (13.30 mm/d) and 26°C (14.13 mm/d), but a significant difference could be observed only under 22°C.

Following the increase of temperature below 22°C, a sharp increase in the rate of Colletotrichum mycelial growth was uniformly observed in all five strains (Fig. 2b). With the exception of Cf: CGMCC3.17371, both C. siamense and C. gloeosporioides strains grew at a higher speed from 22°C to 26°C, although the increase was minor than that observed below 22°C. Statistics analysis suggested that all four C. siamense and C. gloeosporioides strains have similar thermal responses during 10–26°C, while the growth response of Cf: CGMCC3.17371 to temperature changes was significantly different from the rest strains.

These observations were not completely meeting with our previous study (Ji et al. 2023). In that work, the average mycelial growth of these five strains were not significantly different from each other during five days under 22°C. While incubated at 26°C for four days, Cf: CGMCC3.17371 and Cg:JSH-7-1 grew at a speed significantly higher than that of Cs:GQHAH2. In a way, current work provided more accurate comparison and distinguishment for the hypha growth of these Colletotrichum strains in an identical duration (3 d).

Polynomial curve fitting for the temperature responses of Colletotrichum mycelium growth

The generalized beta-function of nonlinear regression model (Hau et al. 1985) has been successfully used for fitting Colletotrichum mycelium growth in relation to temperatures from 22°C to 36°C (Ji et al. 2023). Currently, a series of derivations in SPSS software indicated that the generalized beta-function was not applicable to the low temperature interval from 10°C to 26°C (data omitted). As the growth of fungi plotted against temperature might follow a quadratic parabola (Hau and Kranz 1990), a polynomial function was used to fit the mycelial growth rates in this study (Eq. 1, Fig. S1, Table 1). The coefficient of determination (R²) value was an index of model fitting used to quantify the strength of the relationship between the response variable and the dependent variable. As shown in Table 1, all R² and adjusted R² values in current modelling were greater than 0.95.

Table 1

Response surfaces for mycelium growth rate of different *Colletotrichum* strains as a function of temperature described by the equation: Y = b0 + b1*X^1 + b2*X^2
Fungal strains	Cs:GQHAH2	Cs:Nj-2	Cs:GQH ZJ19	Cf:CGMCC3.17371	Cg:JSH-7-1
b0	-14.48051 ± 0.99366	-12.42774 ± 1.20755	-12.94563 ± 1.2914	-13.30115 ± 1.49075	-16.71172 ± 0.98774
b1	1.80004 ± 0.11816	1.51054 ± 0.14359	1.52446 ± 0.15356	1.61068 ± 0.17859	2.07545 ± 0.11745
b2	-0.02732 ± 0.00325	-0.019 ± 0.00395	-0.01773 ± 0.00423	-0.02393 ± 0.00495	-0.03498 ± 0.00323
Sum of squared residuals	25.95995	38.3392	43.84781	51.98874	25.65142
R²	0.98059	0.97192	0.97199	0.95251	0.9811
Adjusted R²	0.97991	0.97094	0.97101	0.95069	0.98044

In this experiment, the fastest mycelial growth was observed at 26°C, when the model curve still showed an increasing trend for all Colletotrichum strains (Fig. S1), which was consistent with their optimum temperature above 26°C proposed based on the generalized beta-function (Ji et al. 2023). The growth trend of C. fructicola strain was obviously the lowest at different temperatures. C. gloeosporioides s.s. growth displayed minor advantage during 10–22°C, which was not easily distinguished from the patterns of C. siamense. From 26°C on, three C. siamense strains consistently exhibited slightly faster trend in radial mycelium growth than C. gloeosporioides s.s.. In brief, the polynomial fitting conformed to the quadratic function curve shed lights on the relative growth superiority of these Colletotrichum strains and the corresponding temperature ranges.

Pathogenicity of Colletotrichum strains to two strawberry hosts under 14°C and 22°C

The pathogenicity of five Colletotrichum strains were investigated on two strawberry hosts with varying susceptibility under 14°C and 22°C. All strains were pathogenic on the wounded leaves of F. vesca and F. × ananassa, but the resulted disease severity varied with temperature, host type, fungal strain and time post inoculation. No necrotic lesions occurred on mock-treated leaves of two strawberries at any phase after inoculation, and leaves with typical symptoms were displayed in Fig. 3.

Under 14°C, black necrosis was hardly observed on F. vesca at 3 dpi, and minor necrotic points could be discernible only at 5 dpi after inoculation with Cs:GQHZJ19 and Cf:CGMCC3.17371. By contrast, under the same temperature, on the leaves of the highly susceptible cultivar ‘Benihoppe’, necrosis was obviously present at 3 days post inoculation with Cs:GQHZJ19. Indeed, needle-like necrotic points were also discernible on ‘Benihoppe’ at this stage post inoculation with the rest two C. siamense strains. Till 5 dpi, all five Colletotrichum strains caused necrosis on ‘Benihoppe’ leaves at 14°C, although three C. siamense triggered significantly larger lesions than C. fructicola and C. gloeosporioides s.s.

Under 22°C, inoculation with Cs:Nj2, Cs:GQHZJ19 and Cf:CGMCC3.17371 resulted in needle-like necrotic points on the leaves of F. vesca at 3 dpi. Till 5 dpi, necrosis lesions were easily observed on F. vesca inoculated with all strains except for Cs:GQHAH2. Comparatively, the disease symptoms on F. vesca at 5 dpi were somewhat equivalent to that observed at 3 dpi on ‘Benihoppe’. Actually, the virulence of each fungal strain was remarkably pronounced on the wounded leaves of ‘Benihoppe’ at 5 dpi under 22°C. Both C. fructicola and Cs:GQHZJ19 triggered necrotic symptoms at all 42 inoculation sites per strain after three days’ inoculation at 22°C on ‘Benihoppe’. Up to 5 dpi at 22°C, the number of necrotic spots increased, the area of the necrosis expanded, and every fungus caused necrotic lesions on all 42 inoculation sites per strain.

The above observations were preliminary based on several typical infected leaves. In current work, two independent replications provided generally consistent results on the relative pathogenicity of these fungal strains at certain time post inoculation under distinct temperature and for distinct hosts. Together with disease index calculated from necrosis rating values of all 42 inoculation sites, the percents of disease degree were summarized to show the overall pathogenicity per temperature× host type× fungal strain at each phase of one independent experiment (Fig. 4). Clearly, low temperature such as 14°C limited the pathogenesis in two hosts, while 22°C temperature optimum for both host and pathogen fostered the development of anthracnose necrosis. The pathogenicity of these strains varied with host type, infection duration and temperature.

At 3 dpi under 14°C, the virulence of five strains was too weak to be distinguished from each other on the less susceptible F. vesca. For the same host plant at 3dpi, the relative virulence of five strains under 22°C could be ranked as follows: Cs:GQHZJ19 > Cf:CGMCC3.17371 > Cs:Nj2 > Cg:JSH-7-1 > Cs: GQHAH2. Till 5 dpi on the less susceptible host, the relative pathogenicity of five strains largely ranked as Cs:GQHZJ19 > Cf:CGMCC3.17371 > Cs:Nj2 & Cs:GQHAH2 > Cg:JSH-7-1 independent of temperature. It was hard to tell the virulent one from C. siamense strains Cs:NJ2 and Cs:GQHAH2 for F. vesca.

For the highly susceptible commercial cultivar ‘Benihoppe’, Cs:GQHZJ19 still was the most virulent strain and manifested the highest pathogenicity (Fig. 4). At 3 dpi under either 14°C or 22°C, CGMCC3.17371, Cs:Nj2 and Cs:GQHAH2 triggered similar disease incidence on ‘Benihoppe’, a little more severe than that of Cg: JSH-7-1 and weaker than that of Cs:GQHZJ19. Till 5 dpi, the virulence of five strains except for Cs:GQHZJ19 to ‘Benihoppe’ was largely similar under 14°C. For ‘Benihoppe’, the relative virulence of five strains were the same as that for F. vesca under 22°C at 5 dpi.

Correlation of mycelial growth with C. siamense pathogenicity under 14℃ and 22℃

The above work indicated that the mycelial growth rate of selected C. fructicola strain was always the lowest while its virulence was significantly higher than that of C. gloeosporioides s.s. strain. Clearly, mycelial growth rate did not correlate with Colletotrichum strains across different species. Since the delayed mycelial growth might contribute to the reduction in the pathogenicity of C. gloeosporioides (Zhang et al. 2023), the potential correlation of mycelial growth rate with fungal pathogenicity (disease index) was evaluated among strains of C. siamense. Parametric correlation analysis was performed in SPSS software (Table 2).

Table 2

Parametric correlation analysis of mycelial growth and the pathogenicity of C. *siamense*
Parameter	F. vesca var. Ruegen				F. × ananassa cv. Benihoppe
	14℃		22℃		14℃		22℃
	3dpi	5dpi	3dpi	5dpi	3dpi	5dpi	3dpi	5dpi
Correlation coefficient^#	-0.984	-0.651	0.855	0.958	-0.695	-0.644	0.997^*	0.959
P	0.113	0.549	0.347	0.186	0.511	0.554	0.045	0.183
^#Correlation coefficient for the mycelial growth rate and the disease index caused by C. siamense.
* The correlation was significant (P < 0.05) (2-tailed)

Interestingly, the mycelial growth rate of C. siamense was always negatively correlated at 14°C and positively correlated at 22°C with its pathogenicity to strawberry under the same temperature, independent of host susceptibility degree and time post inoculation, although not at a significant level in most cases. The only exception was that, the mycelial growth rate of these fungal strains at 22℃ was significantly and positively correlated with the disease index on the highly susceptible cultivar ‘Benihoppe’ at three days post inoculation with C. siamense.

Influences of temperature, host genotype and fungal ecotype on Colletotrichum pathogenicity

Furtherly, correlation relationship among "temperature", "host genotype", "fungal ecotype" and "disease index" were investigated via using non-parametric correlation analysis in SPSS. Similar results were obtained when data of all five Colletotrichum strains or only three C. siamense strains were analyzed. Evaluation results for all five strains belong to three Colletotrichum species were shown in Table 3. When the disease index was treated as the dependent variable reflecting fungal pathogenicity, fungal ecotype was not correlated with the pathogenicity at early (3 dpi) or late (5 dpi) infection stage. Notably, "host genotype" was always significantly correlated with disease index, at either early or late infection stage. In contrast to this, ‘temperature’ only significantly correlated with fungal pathogenicity at 5 dpi the late infection stage. This analysis hinted that at the early infection stage, host genotype was the crucial factor holding an extremely significant effect on pathogenesis in a temperature range around 14°C ~ 22°C.

Table 3

Nonparametric correlation of ‘temperature’, ‘host genotype’ and ‘fungal ecotype’ with *Colletotrichum* pathogenicity (‘disease severity’)
			3dpi			5dpi
Method Dependent Parameter Variable			Temperature	Host genotype	Fungal ecotype	Temperature	Host genotype	Fungal ecotype
Spielman Rho	Disease index	Correlation coefficient	0.305	0.638^**	0.000	0.538^*	0.486^*	0.018
		Sig. (2-tailed)	0.112	0.001	1.000	0.014	0.030	0.939
		N	20	20	20	20	20	20
*. At the 0.05 level (2-tailed), the correlation was significant.
**. At the 0.01 level (2-tailed), the correlation was extremely significant.

At 5 dpi, both host genotype and temperature were significantly correlated with disease index. To assess the influence of ‘temperature’ and ‘host genotype’ on disease severity statistically, a regression analysis was performed following a linear function (Eq. 2). From Table 4 it could be seen that the t-value of the analyzed ‘temperature’ was 4.670, the t-value of ‘host genotype’ was 2.306 and the p-value for two factors were less than 0.05, hinting that both ‘temperature’ and ‘host genotype’ had a significant effect on ‘disease index’. VIF value less than 5.0 indicated that the two regression lines were not covariant. Beta was the standardized coefficient for current regression modelling. The larger Beta value indicated that the dependent variable was more responsive to the independent variable, that is, the greater the degree of influence. Obviously, at late infection stage, ‘temperature’ has a greater influence (Beta = 0.703) on pathogenicity (disease index) than ‘host genotype’ (Beta = 0.347). The adjusted R² value suggested that ‘temperature’ and ‘host genotype’ could explain at least 56.9% variation in Colletotrichum fungal pathogenicity to strawberry at late infection stage.

Table 4

Influence of ‘temperature’ and ‘host genotype’ on ‘disease index’ at 5 dpi described as a function: Y = a*X + b
	Non-standardized coefficients¹			Standardized coefficient²
	b	a	Beta		t	p	VIF
Constant	-57.690 ± 16.087				-3.586	0002
Temperature		3.415 ± 0.731		0.703	4.670	0.000	1.000
Host genotype		13.490 ± 5.850		0.347	2.306	0.034	1.000
R²	0.615 0.569
Adjusted R²	0.615 0.569
¹b: the constant of the equation. a: the coefficients for certain independent variable. Dependent variable: disease index (Y).
²Beta is the standardized coefficient of regression modelling. R² value is the coefficient of determination, an indicator of model fit, the closer the value is to 1 the better the fit is.

In this work, mycelial growth modelling based on a polynomial linear regression analysis revealed that C. siamense strains share similar growth trends with a C. gloeosporioides strain during 10–26°C, while significantly different from a C. fructicola strain. Indeed, our current and previous work (Ji et al. 2023) together suggested that C. siamense has prominent vigor during 10–40℃, and the thermotolerant strain Cs:GQHZJ19 also grew fast under 22/26℃.

In current work, Cs:GQHZJ19 was found to be highly pathogenic to both F. vesca and F. × ananassa at 14°C and 22°C. And the relative pathogenicity of three C. siamense strains was largely consistent with previous works on ‘Benihoppe’ at 25°C, i.e., GQHAH2, Nj2 and GQHZJ19, being weakly pathogenic, moderately pathogenic and strongly pathogenic, respectively (Ji et al. 2023; Zhang et al. 2020). However, Cs:GQHAH2 displayed significantly higher virulence to ‘Benihoppe’ than Cs:Nj2 at 5 dpi under 30°C (Ji et al. 2023). Since Cs:GQHZJ19 grew fastest in a wide range of temperature over 22°C, these observations rejected the previous arguments for a potential tradeoff between the fungal tolerance to high temperature and its virulence to susceptible host (Chen et al. 2017). Accordingly, it was proposed that C. siamense whose prevalence is increasingly favored in a global warming context, could do harm to host crops under a wide range of temperatures and will not reduce its potential threaten to agricultural production below 26℃.

Plants and pathogens share a co-evolution full of arms race pronounced as simultaneous development of host resistance and pathogen attack mode (Zhan et al. 2014, 2015). Throughout the co-evolutionary history, plants have evolved qualitative and quantitative resistance to improve their survival when confronted with pathogens (Poland et al. 2009; Lo Iacono et al. 2012). Host resistance is one of the most important biological factors shaping not only the populations but evolutionary structure of pathogens (McDonald and Linde 2002). Current statistic analysis enabled the evaluation of factors affecting Colletotrichum risk on strawberry. Our analysis supported that host genotype always significantly affected Colletotrichum pathogenicity. The decisive role of strawberry genotype in defeating Colletotrichum fungi was especially prominent at the early infection stage. Again, breeding novel strawberry with improved resistance to Colletotrichum fungi is the best resolution for managing anthracnose in field.

Temperature is a crucial environmental factor affecting almost all aspects of biological and biochemical processes (Nadeem et al. 2014; Park et al. 2011). Concerning for the interaction between strawberry and Colletotrichum fungus, current work suggested that ‘temperature’ might not hold a significant influence at the early infection stage at 14/22°C. However, ‘temperature’ surpassed ‘host genotype’ (resistance) at the late infection stage in determining the final outcome of pathogen-host interaction. In addition, fungal ecotype was not correlated with anthracnose severity.

This preliminary work tried to address questions from previous work based on selected five representative Colletotrichum strains. To evaluate the biology and risk (virulence) of Colletotrichum strains (especially C. siamense) furtherly, more fungal strains are required for characterization in a wider temperature range. Moreover, future investigation on the temperature requirements of C. siamense in sporulation, conidial germination, and the formation of mycelial appressoria might provide a complete and clear scene on the thermal biology and effective management of this species.

Acknowledgements

The authors gratefully acknowledge the assistance of Zi-Yi Li and Ying Ji for their discussion and guidance in fungal culture, diameter measuring, inoculation and modeling. We thank Ju-Fang Dai and Xian-Hua Dai for their supports in the establishment of plug seedlings. We would also like to show our gratitude to Cai-Ying Wu and Ji-Hua Jin for their assistance in the lab work. Thanks are due to anonymous reviewers for valuable comments which refined this manuscript.

Author Contributions: XL, CG, KD and QG conceived the study and designed the experiments. XL drafted the manuscript. XL, XH, SC, JY and FL performed experiments. XL, CG, YH and KD performed data analysis and interpretation. KD and QG contributed to revision of the manuscript. All authors approved the submitted version.

Funding

This work was partially funded by Science and Technology Commission of Shanghai Municipality (Key Program, 20392001500).

Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethical approval The manuscript does not contain experiments using animals and human studies.

Data Availability Statement: The datasets generated during and analyzed during the current study are available from the corresponding author Ke Duan ([email protected]) on reasonable request.

Amil-Ruiz F, Blanco-Portales R, Muñoz-Blanco J, Caballero José L (2011) The strawberry plant defense mechanism: a molecular review. Plant Cell Physiol 52:1873-1903. https://doi.org/10.1093/pcp/pcr136
Chen F, Duan GH, Li DL, Zhan J (2017) Host resistance and temperature dependent evolution of aggressiveness in the plant pathogen Zymoseptoria tritici. Front Microbiol 8:1217. https://doi.org/10.3389/fmicb.2017.01217
Chung, PC, Wu, HY, Wang, YW, et al (2020) Diversity and pathogenicity of Colletotrichum species causing strawberry anthracnose in Taiwan and description of a new species, Colletotrichum miaoliense sp. nov.. Sci Rep 10:14664. https://doi.org/10.1038/s41598-020-70878-2
Davis T, Denoyes-Rothan B, Lerceteau-Kohler E (2007) Strawberry. Genome Mapping and Molecular Breeding in Plants IV: Fruits and Nuts. Springer 4:189-206. https://doi.org/10.1007/978-3-540-34533-6_8
da Silva LL, Moreno HLA, Correia HLN, Santana MF, de Queiroz MV (2020) Colletotrichum: species complexes, lifestyle, and peculiarities of some sources of genetic variability. Appl Microbiol 104: 1891-1904. https://doi.org/10.1007/s00253-020-10363-y
Damm U, O'Connell RJ, Groenewald JZ, Crous PW (2014) The Colletotrichum destructivum species complex - hemibiotrophic pathogens of forage and field crops. Stud Mycol 79:49-84. https://doi.org/10.1016/j.simyco.2014.09.003
Dubrulle G, Pensec F, Picot A, Rigalma K, Pawtowski A, et al (2020) Phylogenetic Diversity and Effect of Temperature on Pathogenicity of Colletotrichum lupini. Plant Dis 104:938-950. https://doi.org/10.1094/PDIS-02-19-0273-RE
Edger PP, Poorten TJ, VanBuren R, et al (2019) Origin and evolution of the octoploid strawberry genome. Nat Genet 51:541-547. https://doi.org/10.1038/s41588-019-0356-4
He L, Li X, Gao, Y, Li, B, Mu W, Liu F (2019) Characterization and Fungicide Sensitivity of Colletotrichum spp. from Different Hosts in Shandong, China. Plant Dis 103:34-43. https://doi.org/10.1094/PDIS-04-18-0597-RE
Hau B, Kranz J (1990) Mathematics and Statistics for Analyses in Epidemiology. In: Kranz, J. (eds) Epidemics of Plant Dis 13. https://doi.org/10.1007/978-3-642-75398-5_2
Hau B, Eisensmith SP, Kranz J (1985) Construction of temporal models: II. Simulation of aerial epidemics. In: Gilligan CA (ed) Mathematical modelling of crop disease. Academic Press, London.
Hancock J (1999) Strawberries. CABI, Wallingford, UK.
Howard CM, Maas JL, Chandler CK, Albregts EE (1992) Anthracnose of strawberry caused by the Colletotrichum complex in Florida. Plant Dis 76:976-981. https://doi.org/10.1094/pd-76-0976
Han YC, Zeng XG, Xiang FY, Ren L, Chen FY, Gu YC (2016) Distribution and Characteristics of Colletotrichum spp. Associated with Anthracnose of Strawberry in Hubei, China. Plant Dis 100:996-1006. https://doi:10.1094/PDIS-09-15-1016-RE
Ji B, Zhang L, Xing D, Zhang G (2014) Disease occurrence and resistance of 11 strawberry cultivars to anthracnose in the field. Plant Pro 40:123-126. (in Chinese). https://doi.org/10.3969/j.issn.
Ji Y, Geng CN, Song LL, Zhang LQ, Yang J, Gao QH (2023) Different responses to elevated temperature in the representative strains of strawberry pathogenic Colletotrichum spp. from eastern China. Mycol Prog 22:3. https://doi.org/10.1007/s11557-022-01852-7
Ji Y, Li X, Gao QH, Geng CN, Duan K (2022) Colletotrichum species pathogenic to strawberry: discovery history, global diversity, prevalence in China, and the host range of top two species. Phytopathol Res 4:42. https://doi.org/10.1186/s42483-022-00147-9
Liu F, Ma ZY, Hou LW, Diao YZ, Wu WP, Damm U, Song S, Cai L (2022) Updating species diversity of Colletotrichum, with a phylogenomic overview. Stud Mycol 101:1-56. https://doi.org/10.3114/sim.2022.101.01
Lo Iacono G, van den Bosch F, Paveley N (2012) The evolution of plant pathogens in response to host resistance: factors affecting the gain from deployment of qualitative and quantitative resistance. J Theor Biol 304:152-163. http://dx.doi.org/10.1016/j.jtbi.2012.03.033
McDonald BA, Linde C (2002) Pathogen population genetics, evolutionary potential, and durable resistance. Annu Rev Phytopathol 40:349-379. https://doi.org/10.1146/annurev.phyto.40.120501.101443
Moreira RR, Zielinski EC, Castellar C, et al (2021) Study of infection process of five species of Colletotrichum comparing symptoms of glomerella leaf spot and bitter rot in two apple cultivars. Eur J Plant Pathol 159:37-53. https://doi.org/10.1007/s10658-020-02138-y
Munir M, Amsden B, Dixon E, Vaillancourt L, Gauthier NAW (2016) Characterization of Colletotrichum species causing bitter rot of apples in Kentucky orchards. Plant Dis 100:2194-2203. https://doi.org/10.1094/PDIS-10-15-1144-RE
Ngugi HK, Julian AM, King SB, Peacocke B J (2000) Epidemiology of sorghum anthracnose (Colletotrichum sublineolum) and leaf blight (Exserohilum turcicum) in Kenya. Plant Pathol 49:129-140. https://doi.org/10.1046/j.1365-3059.2000.00520.x
Nadeem SM, Ahmad M, Zahir ZA, Javaid A, Ashraf M (2014) The role of mycorrhizae and plant growth promoting rhizobacteria (PGPR) in improving crop productivity under stressful environments. Biotech 32:429-448. https://doi.org/10.1016/j.biotechadv.2013.12.005
Oosumi T, Gruszewski H, Blischak L, Baxter A, Wadl P, Shuman J, et al (2006) High-efficiency transformation of the diploid strawberry (Fragaria vesca) for functional genomics. Planta 223:1219-1230. https://doi.org/10.1007/s00425-005-0170-3
O’Connell RJ, Thon MR, Hacquard S, Amyotte SG, Kleemann J, et al (2012) Life-style transitions in plant pathogenic Colletotrichum fungi deciphered by genome and transcriptome analyses. Nat Genet 44:1060-1065. https://doi.org/10.1038/ng.2372
Poland JA, Balint-Kurti PJ, Wisser RJ, Pratt RC, Nelson RJ (2009) Shades of gray: the world of quantitative disease resistance. Trends Plant Sci 14:21-29. https://doi.org/10.1016/j.tplants.2008.10.006
Park HJ, Kim WY, Park HC, Lee SY, Bohnert HJ, Yun DJ (2011) SUMO and SUMOylation in plants. Mol Cell 32:305-316. https://doi.org/10.1007/s10059-011-0122-7
Ren XJ, Liang Y, Lu JP, Yang BR, Dai FM (2008) Identification of Colletotrichum species from strawberry in Shanghai. Acta Phytopathol Sin 3:325-328 (in Chinese).
Rueden CT, Schindelin J, Hiner M, Dezonia BE, Walter AE (2017) Image J2: ImageJ for the next generation of scientific image data. BMC Bioinform 18:529. https://doi.org/10.1186/s12859-017-1934-z
Salotti I, Ji T, Rossi V (2022) Temperature requirements of Colletotrichum spp. belonging to different clades. Front Plant Sci 13:953760. https://doi.org/10.3389/fpls.2022.953760
Sharma M, Kulshrestha S (2015) Colletotrichum gloeosporioides: an anthracnose causing pathogen of fruits and vegetables. Biosci Biotechnol Res Asia 12:1233-1246. https://doi.org/10.13005/bbra/1776
Soares-Colletti AR, Lourenço SA (2014) Effect of temperature, wetness duration and cultivar on the development of anthracnose in guava fruits. Summa Phytopathol 40:307-312. https://doi.org/10.1590/0100-5405/1988
Talhinhas P, Baroncelli R (2021) Colletotrichum species and complexes: geographic distribution, host range and conservation status. Fungal Divers 110:109-198. https://doi.org/10.1007/s13225-021-00491-9
Velásquez AC, Castroverde CDM, He SY (2018) Plant–pathogen warfare under changing climate conditions. Curr Biol 28:619-634. https://doi.org/10.1016/j.cub.2018.03.054
Weir BS, Johnston PR, Damm U (2012) The Colletotrichum gloeosporioides species complex. Stud Mycol 73:115-180. https://doi.org/10.3114/sim0011
Wilson AM, Wilken PM, van der Nest MA, Wingfield MJ, Wingfield BD (2019) It's all in the genes: the regulatory pathways of sexual reproduction in filamentous Ascomycetes. Genes 10:330. https://doi.org/10.3390/genes10050330
Zhan JS, Thrall PH, Burdon JJ (2014) Achieving sustainable plant disease management through evolutionary principles. Trends Plant Sci 19:570-575. https://doi.org/10.1016/j.tplants.2014.04.010
Zhan JS, Thrall PH, Papaix J, Xie LH, Burdon JJ (2015) Playing on a pathogen’s weakness: using evolution to guide sustainable plant disease control strategies. Annu Rev Phytopathol 53:19-43. https://doi.org/10.1146/annurev-phyto-080614-120040
Zhang LQ, Song LL, Xu X, Zou XK, Duan K, Gao QH (2020) Characterization and fungicide sensitivity of Colletotrichum species causing strawberry anthracnose in eastern China. Plant Dis 104: 1960-1968. https://doi.org/10.1094/PDIS-10-19-2241-RE
Zhang QY, Zhang LQ, Song LL, Duan K, Li N, Wang YX, Gao QH (2016) The different interactions of Colletotrichum gloeosporioides with two strawberry varieties and the involvement of salicylic acid. Hort Res 3:16007. https://doi.org/10.1038/hortres.2016.7

Fig.S1.tif
Fig. S1Response curves for mycelium growth of five Colletotrichum strains as a polynomial of temperature. Mycelial growth curves of five Colletotrichumstrains visualized the radial growth rates of C. siamense (GQHAH2, Nj-2, GQHZJ19), C. fructicola (CGMCC3.17371) and C. gloeosporioidess.s. (JSH-7-1) at five temperatures for 3 days in darkness. In an independent experiment, 12 experimental values of mycelial growth rate were collected for each temperature × strain combination. Smoothing curves were plotted according to the equation Y = b0+ b1X^1 + b2X^2. See Table 1 for details

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The variations of five Colletotrichum strains from strawberry in mycelial growth and pathogenicity below 26℃

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Abstract

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Introduction

Materials and methods

Plant materials and growth conditions

Fungal strains

Characterizing the growth of mycelium

Preparation of inoculum

Pathogenicity assay

Model fitting and statistical analysis

Results

Discussion

Declarations

References

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