Impact of Faba Bean-Seed Rhizobial Inoculation on Microbial Activity in the Rhizosphere Soil during Growing Season

Inoculation of legume seeds with Rhizobium affects soil microbial community and processes, especially in the rhizosphere. This study aimed at assessing the effect of Rhizobium inoculation on microbial activity in the faba bean rhizosphere during the growing season in a field experiment on a Haplic Luvisol derived from loess. Faba bean (Vicia faba L.) seeds were non-inoculated (NI) or inoculated (I) with Rhizobium leguminosarum bv. viciae and sown. The rhizosphere soil was analyzed for the enzymatic activities of dehydrogenases, urease, protease and acid phosphomonoesterase, and functional diversity (catabolic potential) using the Average Well Color Development, Shannon-Weaver, and Richness indices following the community level physiological profiling from Biolog EcoPlate™. The analyses were done on three occasions corresponding to the growth stages of: 5–6 leaf, flowering, and pod formation. The enzymatic activities were higher in I than NI (p < 0.05) throughout the growing season. However, none of the functional diversity indices differed significantly under both treatments, regardless of the growth stage. This work showed that the functional diversity of the microbial communities was a less sensitive tool than enzyme activities in assessment of rhizobial inoculation effects on rhizosphere microbial activity.


Introduction
Gram-negative soil bacteria of the genus Rhizobium play a very important role in agriculture. They form a symbiotic relationship with leguminous crops resulting in biological nitrogen fixation and thereby reduction of the requirements for added nitrogenous fertilizer during the growing season. Rhizobium symbiosis with legumes produces 50% of 175 million tons of total biological N2 fixation annually worldwide [1]. Therefore, inoculation of legumes with efficient rhizobia at sowing is one of the most important and agronomically eco-friendly practices used for improvement of N fixation. Denton et al. [2] observed that nodule dry matter increased in soil with an increasing rate of inoculation. Besides enhanced nodulation and nitrogen fixation, rhizobial seed inoculation can stimulate production of phytohormones, siderophores, and HCN (hydrogen cyanide) as well as microbial diversity and structure, potentially enhancing plant growth-promoting rhizobacteria [3,4]. Rhizobial inoculation (with R. leguminosarum) enhanced phosphate solubilization [1,5] as well as P and N uptake and Fe content in lettuce and carrots [6]. Inoculation with a R. gallicum strain induced growth of bacterial communities that had been often reported as PGPM (plant growth-promoting microorganisms) [3]. The extent of these changes was also seen in the next rotation crop. Therefore, rhizobial inoculation resulted in increased shoot growth, number of pods, and grain yield of faba bean [2] and lentil [5], compared with non-inoculated controls.
Using T-RFLP (Terminal Restriction Fragment Length Polymorphism) analysis, Trabelsi et al. [4] showed that inoculation of common bean with rhizobial strains resulted in a highly significant increase in the TRF (Terminal Restriction Fragments) number (51 TRFs), compared to non-inoculated plants (13 TRFs). Additionally, among the total number of 84 TRFs, 23 were specifically induced by inoculation, indicating that inoculation with rhizobia increased microbial diversity and structure.
Rhizobia can also serve as biological control agents of some plant pathogens in legume and non-legume plants [7]. In fields infested with Pythium spp., inoculation with Rhizobium leguminosarum significantly increased seedling emergence in pea and sugar beets [8] and reduced the incidence of a disease induced by soil-borne pathogens of pea and lentil [9]. Treatment of faba bean seeds with R. leguminosarum under soil infestation conditions by R. solani caused significant reduction in damping-off as compared to the untreated control [10].
Rhizobial seed inoculation may have a significant influence on the growth and composition of the microbiome as well as associated synthesis and release of enzymes into soil, especially in the rhizosphere. The rhizosphere is a narrow zone of soil that is influenced by root exudates and inhabited by most microorganisms (bacteria and fungi), including those beneficially affecting soil health and ecosystem functioning [11]. Rhizobacteria with growth-promoting and pathogen-suppressive capability were isolated from healthy chickpea (Cicer arietinum L.) plants and identified as Pseudomonas and Bacillus [12].
Little information is available about the effect of Rhizobium inoculation on the soil microbial activity in the faba bean rhizosphere. Faba bean is an important leguminous crop. It occupies ca. 5.3% of the sown area of fodder legumes in Poland [13]. The objectives of this study were (1) to determine the effect of inoculation of faba bean seeds with Rhizobium on soil microbial activity; and (2) to compare the activity of actual soil microbial community using enzyme activities with the functional diversity of the cultivable community using Biolog Ecoplates of field soil with low resident rhizobia. To date, according to our knowledge, no studies with faba bean concerning the microbial effect of inoculation with rhizobia were conducted using both approaches simultaneously.

Enzyme Activities
All enzymatic activities (except for protease activity at T1 and T2 and acid phosphomonoesterase at T3) were higher in inoculated (I) than non-inoculated (NI) (p < 0.05) throughout the growing season although the extent of the differentiation was related to the type of the microbial activity and measurement occasion (Figure 1). At T1 and T2 (5-6 leaf and flowering stages, respectively), the relative differences between the two treatments were appreciably higher in urease activity (72%-143%) and dehydrogenase activity (55%-70%) than in the activities of acid phosphomonoesterase (8%-11%) and protease (3%-25%), whereas at T3 the differences amounted to 86% in protease and 102% in urease activities.
When annual averages were taken into consideration, all the evaluated enzymatic activities were improved by the inoculation of the seeds with rhizobia. The most pronounced improvement produced by the inoculation was noticed for urease (104%), while acid phosphomonoesterase activity was changed to the lowest extent (7%). However, this increase for protease was insignificant. The above results indicate that the enzymatic activities in our study were not similarly affected by the Rhizobium inoculation during the growing season. The relatively high sensitivity of urease activity and dehydrogenase activity at growth stages T1 (5-6 leaf) and T2 (flowering) indicate that Rhizobium inoculation has great potential for the cycling of N and production of adenosine triphosphate through oxidation of organic matter in the soil, respectively. However, the less pronounced increases in the activities of acid phosphomonoesterase and protease indicate respectively low release of both inorganic phosphorus (orthophosphate) from organic phosphomonesters [14] and protein N at the hydrolysis [15,16].
The changes in a majority of the enzymatic activities between the measurement occasions were statistically different (p < 0.05) both in NI and I treatments. Irrespective of the treatment, maximum values of dehydrogenase and protease activities were noted at T2, urease activity at T3, and the activity of acid phosphomonoesterase at T1. The maximum values of dehydrogenase and protease activities at T2 (flowering) can be linked to abundant root size and organic carbon from root exudates in the rhizosphere at this growth stage and hence increasing microbial populations contributing to release of these enzymes [11]. This effect was more pronounced in I than NI. The Rhizobium inoculation and enhanced enzymatic activity may improve plant growth through soil nutrient enrichment and increase of resistance against plant pathogens [17]. The changes in a majority of the enzymatic activities between the measurement occasions were statistically different (p < 0.05) both in NI and I treatments. Irrespective of the treatment, maximum values of dehydrogenase and protease activities were noted at T2, urease activity at T3, and the activity of acid phosphomonoesterase at T1. The maximum values of dehydrogenase and protease activities at T2 (flowering) can be linked to abundant root size and organic carbon from root exudates in the rhizosphere at this growth stage and hence increasing microbial populations contributing to release of these enzymes [11]. This effect was more pronounced in I than NI. The Rhizobium inoculation and enhanced enzymatic activity may improve plant growth through soil nutrient enrichment and increase of resistance against plant pathogens [17].

Community Level Physiological Profiling (CLPP)
AWCD (average well-color development) was higher in T2 than T1 and T3 under both treatments (Table 1). However, the differences between both treatments were not significant, regardless of the sampling time. Similarly, annual averages did not differ after the rhizobial inoculation. The R index did not differ between the NI and I treatments in all sampling terms and for the annual mean. However, it decreased significantly in T3, in comparison with T2 under I. Although H did not differ between both treatments in individual sampling terms, it significantly increased under I in T3, compared to T1 and T2. The mean value of H was higher under I than NI.

Community Level Physiological Profiling (CLPP)
AWCD (average well-color development) was higher in T2 than T1 and T3 under both treatments (Table 1). However, the differences between both treatments were not significant, regardless of the sampling time. Similarly, annual averages did not differ after the rhizobial inoculation. The R index did not differ between the NI and I treatments in all sampling terms and for the annual mean. However, it decreased significantly in T3, in comparison with T2 under I. Although H did not differ between both treatments in individual sampling terms, it significantly increased under I in T3, compared to T1 and T2. The mean value of H was higher under I than NI.  Figure 2 presents the bond distances between the treatments, where clustering was evaluated using the carbon utilization patterns of the substrates. Taking into consideration Sneath's criterion 66%, two groups were distinguished. A similar response was noted under I T3 and I T1 (group 1) in terms of carbon substrate utilization. These findings were supported by the carbon substrate utilization intensity (Figure 3). A lower degree of substrate utilization was observed in group 1 than 2. The lower rate of utilization of substrates by group 1 than 2 was found for N-Acetyl-D-Glucosamine, D-Galactonic Acid γ-Lactone, L-Asparagine, D-Cellobiose, α-D-Lactose, D-Malic Acid, L-Arginine, β-Methyl-D-Glucoside, and Itaconic Acid. Significant differences among the treatments were observed in the utilization patterns of categorized substrates (Figure 4). The highest differences between the NI and I treatment were noted for polymers in T2 and carboxylic acids in T3 when both categorized substrates were used to a lesser extent under I than NI. Figure 2 presents the bond distances between the treatments, where clustering was evaluated using the carbon utilization patterns of the substrates. Taking into consideration Sneath's criterion 66%, two groups were distinguished. A similar response was noted under I T3 and I T1 (group 1) in terms of carbon substrate utilization. These findings were supported by the carbon substrate utilization intensity (Figure 3). A lower degree of substrate utilization was observed in group 1 than 2. The lower rate of utilization of substrates by group 1 than 2 was found for N-Acetyl-D-Glucosamine, D-Galactonic Acid γ-Lactone, L-Asparagine, D-Cellobiose, α-D-Lactose, D-Malic Acid, L-Arginine, β-Methyl-D-Glucoside, and Itaconic Acid. Significant differences among the treatments were observed in the utilization patterns of categorized substrates (Figure 4). The highest differences between the NI and I treatment were noted for polymers in T2 and carboxylic acids in T3 when both categorized substrates were used to a lesser extent under I than NI.

66%
Group II Group I  Figure 2 presents the bond distances between the treatments, where clustering was evaluated using the carbon utilization patterns of the substrates. Taking into consideration Sneath's criterion 66%, two groups were distinguished. A similar response was noted under I T3 and I T1 (group 1) in terms of carbon substrate utilization. These findings were supported by the carbon substrate utilization intensity (Figure 3). A lower degree of substrate utilization was observed in group 1 than 2. The lower rate of utilization of substrates by group 1 than 2 was found for N-Acetyl-D-Glucosamine, D-Galactonic Acid γ-Lactone, L-Asparagine, D-Cellobiose, α-D-Lactose, D-Malic Acid, L-Arginine, β-Methyl-D-Glucoside, and Itaconic Acid. Significant differences among the treatments were observed in the utilization patterns of categorized substrates (Figure 4). The highest differences between the NI and I treatment were noted for polymers in T2 and carboxylic acids in T3 when both categorized substrates were used to a lesser extent under I than NI.   I T3  I T1  NI T3  I T2  NI T2  NI T1  30   40   50   60   70   80   90   100   110 Bond distance (%)

66%
Group II Group I  Analyses of variance (Table 2) showed that the functional diversity of the microbial communities was a less sensitive tool for assessment of rhizobial inoculation effects than soil enzyme activities, indicating that soil enzyme activities may reveal more about microbial activity of soil. This may be related to the fact that CLPP could select rare, less-dominant, but culturable members of the community that have adapted to rapid growth on available substrates. As opposed to the CLPP, soil enzyme activity is a cultivation-independent method and can reflect the functioning of the microbial community. It is worth noting that soil enzyme activities (Figure 1), compared to the functional diversity via Biolog EcoPlates (Table 1), were more sensitive to the rhizobial inoculation throughout the growing season. This result is in agreement with earlier findings indicating that the Biolog method can be suitable for detecting changes in substrate availability for microorganisms shortly after soil modification than during a later period [18].
Overall, the results from the present study on the enzyme activity and functional diversity of a rhizosphere environment agree well with earlier results indicating that root-mediated processes enhance soil aggregation and plant drought resistance and affect soil acidity and accessibility of nutrients to plants [11].  Analyses of variance (Table 2) showed that the functional diversity of the microbial communities was a less sensitive tool for assessment of rhizobial inoculation effects than soil enzyme activities, indicating that soil enzyme activities may reveal more about microbial activity of soil. This may be related to the fact that CLPP could select rare, less-dominant, but culturable members of the community that have adapted to rapid growth on available substrates. As opposed to the CLPP, soil enzyme activity is a cultivation-independent method and can reflect the functioning of the microbial community. It is worth noting that soil enzyme activities (Figure 1), compared to the functional diversity via Biolog EcoPlates (Table 1), were more sensitive to the rhizobial inoculation throughout the growing season. This result is in agreement with earlier findings indicating that the Biolog method can be suitable for detecting changes in substrate availability for microorganisms shortly after soil modification than during a later period [18].
Overall, the results from the present study on the enzyme activity and functional diversity of a rhizosphere environment agree well with earlier results indicating that root-mediated processes enhance soil aggregation and plant drought resistance and affect soil acidity and accessibility of nutrients to plants [11]. of the carbon utilization patterns of the substrates on the Biolog EcoPlate TM between the treatments, a dendrogram was prepared with scaled bond distances on the axis (method of Ward) and boundary marked according to Sneath's criterion (66%). The results were standardized according to AWCD in each microplate in order to remove the inoculum density effects [28].

Conclusions
This work showed that Rhizobium inoculation induced a significant and consistent increase in a majority of enzymatic activities in the rhizosphere throughout the vegetative period of faba bean. Rhizobium inoculation can affect selectively and variously the enzymatic activity depending on the enzyme type and plant growth stage. The functional diversity of microbial communities determined using Biolog EcoPlates is a less sensitive tool than enzyme activities in assessment of rhizobial inoculation effects on rhizosphere microbial activity.